Senior data scientist jobs in Salinas, CA - 345 jobs

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. AI & Data - Data Architecture - Senior Manager - Power & Utilities Sector EY is seeking a motivated professional with solid experience in the utilities sector to serve as a Senior Manager who possesses a robust background in Data Architecture, Data Modernization, End to end Data capabilities, AI, Gen AI, Agentic AI, preferably with a power systems / electrical engineering background and having delivered business use cases in Transmission / Distribution / Generation / Customer. The ideal candidate will have a history of working for consulting companies and be well-versed in the fast-paced culture of consulting work. This role is dedicated to the utilities sector, where the successful candidate will craft, deploy, and maintain large-scale AI data ready architectures. The opportunity You will help our clients enable better business outcomes while working in the rapidly growing Power & Utilities sector. You will have the opportunity to lead and develop your skill set to keep up with the ever-growing demands of the modern data platform. During implementation you will solve complex analytical problems to bring data to insights and enable the use of ML and AI at scale for your clients. This is a high growth area and a high visibility role with plenty of opportunities to enhance your skillset and build your career. As a Senior Manager in Data Architecture, you will have the opportunity to lead transformative technology projects and programs that align with our organizational strategy to achieve impactful outcomes. You will provide assurance to leadership by managing timelines, costs, and quality, and lead both technical and non-technical project teams in the development and implementation of cutting-edge technology solutions and infrastructure. You will have the opportunity to be face to face with external clients and build new and existing relationships in the sector. Your specialized knowledge in project and program delivery methods, including Agile and Waterfall, will be instrumental in coaching others and proposing solutions to technical constraints. Your key responsibilities In this pivotal role, you will be responsible for the effective management and delivery of one or more processes, solutions, and projects, with a focus on quality and effective risk management. You will drive continuous process improvement and identify innovative solutions through research, analysis, and best practices. Managing professional employees or supervising team members to deliver complex technical initiatives, you will apply your depth of expertise to guide others and interpret internal/external issues to recommend quality solutions. Your responsibilities will include: As Data Architect - Senior Manager, you will have an expert understanding of data architecture and data engineering and will be focused on problem-solving to design, architect, and present findings and solutions, leading more junior team members, and working with a wide variety of clients to sell and lead delivery of technology consulting services. You will be the go-to resource for understanding our clients' problems and responding with appropriate methodologies and solutions anchored around data architectures, platforms, and technologies. You are responsible for helping to win new business for EY. You are a trusted advisor with a broad understanding of digital transformation initiatives, the analytic technology landscape, industry trends and client motivations. You are also a charismatic communicator and thought leader, capable of going toe-to-toe with the C-level in our clients and prospects and willing and able to constructively challenge them. Skills and attributes for success To thrive in this role, you will need a combination of technical and business skills that will make a significant impact. Your skills will include: Technical Skills Applications Integration Cloud Computing and Cloud Computing Architecture Data Architecture Design and Modelling Data Integration and Data Quality AI/Agentic AI driven data operations Experience delivering business use cases in Transmission / Distribution / Generation / Customer. Strong relationship management and business development skills. Become a trusted advisor to your clients' senior decision makers and internal EY teams by establishing credibility and expertise in both data strategy in general and in the use of analytic technology solutions to solve business problems. Engage with senior business leaders to understand and shape their goals and objectives and their corresponding information needs and analytic requirements. Collaborate with cross-functional teams (Data Scientists, Business Analysts, and IT teams) to define data requirements, design solutions, and implement data strategies that align with our clients' objectives. Organize and lead workshops and design sessions with stakeholders, including clients, team members, and cross-functional partners, to capture requirements, understand use cases, personas, key business processes, brainstorm solutions, and align on data architecture strategies and projects. Lead the design and implementation of modern data architectures, supporting transactional, operational, analytical, and AI solutions. Direct and mentor global data architecture and engineering teams, fostering a culture of innovation, collaboration, and continuous improvement. Establish data governance policies and practices, including data security, quality, and lifecycle management. Stay abreast of industry trends and emerging technologies in data architecture and management, recommending innovations and improvements to enhance our capabilities. To qualify for the role, you must have A Bachelor's degree required in STEM 12+ years professional consulting experience in industry or in technology consulting. 12+ years hands-on experience in architecting, designing, delivering or optimizing data lake solutions. 5+ years' experience with native cloud products and services such as Azure or GCP. 8+ years of experience mentoring and leading teams of data architects and data engineers, fostering a culture of innovation and professional development. In-depth knowledge of data architecture principles and best practices, including data modelling, data warehousing, data lakes, and data integration. Demonstrated experience in leading large data engineering teams to design and build platforms with complex architectures and diverse features including various data flow patterns, relational and no-SQL databases, production-grade performance, and delivery to downstream use cases and applications. Hands-on experience in designing end-to-end architectures and pipelines that collect, process, and deliver data to its destination efficiently and reliably. Proficiency in data modelling techniques and the ability to choose appropriate architectural design patterns, including Data Fabrics, Data Mesh, Lake Houses, or Delta Lakes. Manage complex data analysis, migration, and integration of enterprise solutions to modern platforms, including code efficiency and performance optimizations. Previous hands‑on coding skills in languages commonly used in data engineering, such as Python, Java, or Scala. Ability to design data solutions that can scale horizontally and vertically while optimizing performance. Experience with containerization technologies like Docker and container orchestration platforms like Kubernetes for managing data workloads. Experience in version control systems (e.g. Git) and knowledge of DevOps practices for automating data engineering workflows (DataOps). Practical understanding of data encryption, access control, and security best practices to protect sensitive data. Experience leading Infrastructure and Security engineers and architects in overall platform build. Excellent leadership, communication, and project management skills. Data Security and Database Management Enterprise Data Management and Metadata Management Ontology Design and Systems Design Ideally, you'll also have Master's degree in Electrical / Power Systems Engineering, Computer science, Statistics, Applied Mathematics, Data Science, Machine Learning or commensurate professional experience. Experience working at big 4 or a major utility. Experience with cloud data platforms like Databricks. Experience in leading and influencing teams, with a focus on mentorship and professional development. A passion for innovation and the strategic application of emerging technologies to solve real-world challenges. The ability to foster an inclusive environment that values diverse perspectives and empowers team members. Building and Managing Relationships Client Trust and Value and Commercial Astuteness Communicating With Impact and Digital Fluency What we look for We are looking for top performers who demonstrate a blend of technical expertise and business acumen, with the ability to build strong client relationships and lead teams through change. Emotional agility and hybrid collaboration skills are key to success in this dynamic role. FY26NATAID What we offer you At EY, we'll develop you with future-focused skills and equip you with world-class experiences. We'll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more. We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $144,000 to $329,100. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $172,800 to $374,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Join us in our team‑led and leader‑enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year. Under our flexible vacation policy, you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well‑being. Are you ready to shape your future with confidence? Apply today. EY accepts applications for this position on an on‑going basis. For those living in California, please click here for additional information. EY focuses on high‑ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities. EY | Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories. EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law. EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at ************************** . #J-18808-Ljbffr

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo. Why Join Us Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day. We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us. About the Team Our team plays a crucial role in ensuring the company's success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you'll be part of a team that's developing new solutions to new challenges. It's working fast, at scale, and we're making a difference. We are looking for talents to join us on this exciting journey! Responsibilities Conduct deep analyses into user behavior, product features and content ecosystem to generate data-driven business insights, improve user experience and support the company's growth initiatives. Analyze large and complex data to discover trends and patterns in data through probability and statistical analysis and automate collection processes. Drive data-informed decisions on experiment launches and measure the impact of product or technical changes. Validate hypotheses, identify product growth opportunities, and influence direction for improvement with analyses, experimentation or other scientific methods. Define and monitor metrics framework to evaluate the performance of products and initiatives and understand root cause of metrics movements. Present information to internal stakeholders using data visualization techniques to deliver product insights and strategy recommendations. Collaborate with cross-functional teams, including data engineers and domain experts, to optimize overall project goals.Qualifications Must have a Master's degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Data Science, Analytics (any), Statistics, Mathematics, or a related field, and 1 year of related work experience; OR a Bachelor's degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Data Science, Analytics (any), Statistics, Mathematics, or a related field, and 3 years of related work experience. Of the required experience, must have 1 year of experience in each of the following: Using SQL queries to analyze large and complex datasets, addressing technical and statistical problems to drive business impact; Conducting exploratory and predictive analysis using Python, R, and/or Scala; Designing A/B tests, conducting statistical analysis, and interpreting A/B test results to provide insights for product features; Cleaning and processing data using relational databases and/or Hadoop Systems; and Developing graphical and visual representations of data using business intelligence tools Excel and Tableau. Type: Full time, 40 hours/week Location: San Jose, CA Salary Range: $174304 - $240000 per year To Apply, click the apply button below. Contact ******************** if you have difficulty submitting resume through the website. TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at ****************************** #IND-DNI

About ByteDance Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. Why Join Us Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day. As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us. About the Team Our team plays a crucial role in ensuring the company's success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you'll be part of a team that's developing new solutions to new challenges. It's working fast, at scale, and we're making a difference. We are looking for talents to join us on this exciting journey! Responsibilities Own and conduct data analysis related to live streaming and real-time communication (RTC) products. Ensure data quality by monitoring event tracking quality, participating in event tracking design reviews, and collaborating with the data engineering team. Build efficient data ETL processes and maintain data SLAs. Develop and maintain a comprehensive live streaming and RTC-related metrics system, including defining indicators, building dashboards, ensuring stability and availability, and conducting root cause analysis for metrics. Perform data analysis based on business requirements, support data analysis for special projects, and provide ongoing data analysis support. Support A/B testing initiatives by optimizing A/B testing processes, producing Libra indicators, providing attribution analysis, and generating A/B testing conclusions and reports. Drive business growth by identifying data optimization opportunities, providing optimization suggestions, and delivering tangible benefits. Develop and refine optimization methodologies over time. Collaborate with cross-functional teams, such as Product Management, Research and Development, and Technical Support, to identify and resolve online issues. Qualifications Must have a Master's degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Machine Learning, Statistics (any), Analytics, Data Science, Mathematics, or a related field, and 2 years of related work experience; OR a Bachelor's degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Machine Learning, Statistics (any), Analytics, Data Science, Mathematics, or a related field, and 5 years of post-bachelor's, progressive related work experience. Of the required experience, must have 2 years of experience in each of the following: Mining, preparing, cleansing, and analyzing structured data using statistical computing languages SQL, Python, and/or R for metrics creation, root cause analysis, and model preprocessing; Using SQL queries and data visualization tools to gather, process, visualize, and analyze large quantities of data to detect trends and anomalies in support of business opportunity identification; Analyzing large quantities of data to detect anomalies using Python and statistical analysis techniques; Developing and maintaining tables, views, indexes, datasets, and/or data pipelines to extract, clean, transform, load and maintain data across multiple databases; and Providing data-driven insights and recommendations to mitigate insufficiencies models based on model performance, regulations, or business requirements. Travel Requirement: International travel required up to 10%. Type: Full time, 40 hours/week Location: San Jose, CA Salary Range: $275850 - $395280 per year To Apply, click the apply button below. Contact *********************** if you have difficulty submitting resume through the website. ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. ByteDance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at ****************************** #IND-DNI

Apple's intelligent systems generate rich, multi-modal data from devices, sensors, software, and services. We're looking for a data scientist who can bring clarity to this complexity - someone who can analyze diverse datasets, surface meaningful insights, and design intuitive tools that help teams understand and improve the intelligence behind Apple products. You'll work across the full data lifecycle: discovering signals in large-scale distributed logs, building search and retrieval mechanisms to make data accessible, and crafting interactive visualizations and evaluations that guide product direction and system performance. Our team works at the intersection of hardware, software, and intelligence. We design the systems, infrastructure, and tools that enable Apple's next generation of AI-driven experiences - from on-device middleware and distributed inference platforms to large-scale data pipelines, interactive analytics, and advanced developer tooling. We collaborate closely with hardware, robotics, ML, design, and platform teams to build end-to-end solutions that are performant, intuitive, and deeply integrated into Apple's ecosystem. The work is hands-on, highly cross-disciplinary, and central to shaping how Apple's intelligent systems evolve. Experience working with data from distributed or real-time systems, robotics, or multi-modal AI Familiarity with information retrieval techniques (ranking, embedding-based search, relevance modeling) Experience collaborating with ML teams on evaluation methodologies, dataset design, or model diagnostics Knowledge of metadata management systems, cataloging approaches, or data documentation strategies Background in statistical modeling, time-series analysis, or anomaly detection Experience with visualization frameworks used for large datasets Understanding of cloud-scale data processing and distributed compute frameworks Proven experience in data science, analytics engineering, or applied research roles Strong proficiency in Python and common data analysis libraries Expertise with data visualization tools or frameworks for building interactive dashboards Experience querying and modeling data in SQL and NoSQL environments Ability to analyze large-scale, high-dimensional, and multi-modal datasets Familiarity with designing or using search and retrieval systems for large-scale data Experience designing KPIs, evaluation metrics, or experiment analyses for complex systems Strong statistical intuition and experience with exploratory data analysis and hypothesis testing Ability to translate complex findings into clear, actionable insights for cross-functional teams Bachelor's or Master's degree in Data Science, Computer Science, Applied Mathematics, or related field, and 5+ years of industry experience

#DS-AVN Our client, a pioneer in reshaping consumer credit using innovative technology, is committed to reducing capital costs. They strongly believe in universal access to capital, crucial in today's capital-based economy, with over $1 trillion in unsecured credit card revolving balances. The journey of credit cards since the '60s, culminating in balances exceeding $1 trillion in 50 years, reveals the existing challenges. Unsecured credit, despite its efficiency in quick underwriting and access to capital in 1-3 days, comes at a high cost (15-25% APR). Conversely, secured capital involves high origination costs and prolonged processes (weeks in underwriting, months for access) but offers cheaper rates ( Innovating the credit landscape, our client introduced a new asset-backed credit card, securing equity in homes, cars, and other assets. This innovation allows them to offer remarkably low APRs to consumers. Their flagship product boasts the world's lowest APR credit card, aiming to change the credit paradigm. Funding: Backed by substantial equity funding of over $250 million, our client comprises a well-capitalized team comprising technology (Microsoft, Facebook) and finance (Square, Discover, CapitalOne, Goldman) experts. With top-tier investors like Founders Fund, Khosla Ventures, Caffeinated Capital, Max Levchin, NYCA, and Sequoia, our client continues to lead the charge in transforming consumer credit. Additionally, they recently secured Series D funding, further solidifying their position in this innovative endeavor. Role: Data Scientist Join a dynamic startup that's pioneering innovative paths in technology across multiple sectors. We are seeking a highly skilled Data Scientist who thrives on analyzing and deriving insights from complex data sets to drive product strategy and business decisions. In this role, you will collaborate closely with diverse teams, including Product, Engineering, Marketing, Sales, Finance, and Data Science, to develop and implement data-driven strategies that enhance product performance and customer satisfaction. Responsibilities: Partner with cross-functional teams to influence product strategies using advanced analytical and scientific methods. Utilize statistical, machine learning, and econometric models on large datasets to measure outcomes, identify causal impacts, and attribute effects. Predict future performance of users or products using robust data-driven methodologies. Design, implement, and launch innovative data science solutions to bolster decision-making at all levels. Analyze experiment results and interpret data to refine product offerings and strategies. Develop and monitor key performance metrics for products, ensuring data accuracy and actionable insights. Lead the enhancement of data collection practices and refine existing data to improve overall data quality. Who Should Apply: Individuals with over 5 years of data science experience and demonstrated thought leadership in the field. Those holding a PhD or MS in a quantitative discipline such as Engineering, Mathematics, Natural Sciences, or Economics. Experts in a scientific computing language (R or Python) and proficient in SQL. Professionals with deep theoretical and practical knowledge in statistics, machine learning, and experimental design. Excellent communicators with strong abilities to convey complex data in a clear and persuasive manner. Experienced in designing and scaling complex modeling solutions from concept through to production. Influential in high-stake decision-making processes with strong project management skills. This position offers an exceptional opportunity to be at the forefront of technological innovation and to shape the future of a fast-growing startup. If you are a motivated Data Scientist eager to make a substantial impact through your analytical expertise and strategic insights, we would love to hear from you. Cash Comp in the range of $200K-$300K.

Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Opportunity: The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling capabilities, and a collaborative working style. The right candidate will have strong intellectual curiosity and passion for achieving business results. An ability to quickly define the problem, research and leverage state-of-the-art modeling techniques, and provide timely recommendations will be essential. Key skills will include a strong analytical mindset, deep understanding of most popular machine learning algorithms and lead key initiatives with integrity and a passion for investigations, problem solving, and troubleshooting. What You'll Be Doing: Identify complex fraud patterns and their technical root causes through detailed data mining and analysis, including identification of sophisticated fraud methods employed by actors who are deliberately trying to avoid detection. Serve as technical SME by sharing new data mining techniques, maintaining technical reference documentation, and interfacing with partner technology teams. Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences. Provide technical guidance for engineering projects that incorporate new data points into the investigation team's toolkit, such as API integrations or internal data transformations. Link Analysis/Graph analytics to find and mitigate deeply-connected fraud networks and detect new accounts being added to these networks Unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies Development of machine learning models Partner with product and engineering team in implementing features and models, and enhancing systems What We Look For In You: Master's degree (or PhD) in Statistics, Mathematics, Operations Research, Computer Science, Economics, Engineering or other quantitative discipline. Bachelor's degree with significant relevant experience will be considered. 4+ years of fraud analytics experience in financial services or FinTechs Crypto/Blockchain experience Deep understanding of modern machine learning techniques / algorithms including GBM, XGBoost, LGBM, etc. Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.); Successful track record of owning and driving large, complex data analysis projects. Demonstrated capacity for innovation and outside-the-box thinking in the creation of new capabilities and processes that are unstructured or exploratory in nature. Experience in a fast-paced startup environment with a strong level of initiative; and Ability and willingness to travel as needed. Strong communicator in both writing and speaking Multi-tasking and strong project management skills Nice to Haves: Hands-on experience/knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.); and Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! OKX Statement: The salary range for this position is $223,661.00 to $268,333.00. The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via Okcoin and OKX internal or external careers site. OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. #LI-HYBRID#LI-ED1 Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX's Candidate Privacy Notice.

QuantumScape is on a mission to transform energy storage with solid-state lithium-metal battery technology. The company's next-generation batteries are designed to enable greater energy density, faster charging and enhanced safety to support the transition away from legacy energy sources toward a lower carbon future. About the team: Manufacturing Quality is a diverse group of engineers and data scientists who bring deep expertise in materials science, electrochemistry, statistics, and machine learning. Our team thrives on data-driven decision-making and a shared commitment to drive continuous improvement to QuantumScape's solid-state battery technology. We work closely with the Manufacturing, Reliability, and R&D, groups to identify failure modes, engineer critical-to-quality specifications, and implement robust control strategies across all process areas. What we need: The Manufacturing Quality team is seeking a mid-level engineer who is proficient with data science methodologies and is excited about improving the quality and reliability of our solid-state Li metal batteries. You will support specification development activities interfacing with multiple cross-functional departments across the company. The ideal candidate has a hard sciences background, statistics and data science experience through coursework or industry, and the ability to communicate complex technical information to a diverse group of stakeholders. If you enjoy problem-solving and thrive in a highly collaborative, fast-paced environment, we'd like to hear from you. What You'll do: * Design and implement new specifications based on in-line metrology inspection systems (e.g. optical, 3D, radiograph) across film, cathode, and cell assembly processes to drive improvements to the quality and reliability of our batteries. * Leverage machine learning or traditional statistics methodologies to identify in-process metrics that are best predictive of electrical performance. Identify strategy to increase cell reliability based on the learnings. * Develop machine learning models to classify components or features based on underlying knowledge. Coordinate labeling, development, validation, and implementation of models. * Define and validate statistically-valid sampling strategies to accept/reject batches based on measurements of a small subset of parts. * Communicate complex technical information to cross-functional stakeholders with refined presentations and weekly write-ups. Propose path forward based on learnings. * Continuously study state-of-the-art data science methodologies through AI-assisted literature review, critically identify best options, and rapidly apply them to internal projects. Skills You'll Need: * B.S. & 3+ years of experience or M.S. & 1+ years of experience is required. Educational background preferably in Materials Science, Chemical Engineering, Chemistry, Physics, or equivalent engineering field. * Strong programming skills with 2+ years of relevant experience through coursework or industry. * Proficiency with Python data science and machine learning libraries, such as Pandas, Scikit-learn, SciPy, TensorFlow, PyTorch, etc. * Proficiency with SQL to query data from database and data warehouse storage (i.e.: GCP's BigQuery) * Industry or academic experience with statistical analysis for manufacturing processes, like regression (i.e.: linear, logistics), t-tests, comparison of different test groups, etc. * Experience developing machine learning models such as tree-based models (i.e.: decision trees, random forest, XGBoost, etc.) or deep learning models (i.e.: neural networks, autoencoders, etc.) to predict binary or continuous outcomes using large, complex datasets. * Excellent written and verbal communication skills to collaborate closely with cross-functional colleagues. Nice to have: * 2+ years of experience in the battery manufacturing industry. * Hands-on experience with battery assembly, failure analysis, or characterization techniques. * Proficiency with AI coding tools to accelerate data analysis and visualization, model development, etc. * Proficiency with SQL to query data from database and data warehouse storage. * Proficiency with JMP, Microsoft Office, VSCode, and Github Copilot. Physical requirements: * Work is performed in an office. * Sitting or standing for extended periods of time. HYBRID: This position is required to work onsite at least 4 days per week to meet the minimum essential duties and requirements of this position. As a data scientist in the Manufacturing Quality team, in-person face-to-face interaction is essential to building authentic relationships, trust, teamwork, and collaboration. Compensation & Benefits: The expected salary range for this role is from $134,400 to $174,700, and a final salary will be determined by the candidate's experience and educational background. QuantumScape also offers an annual bonus and a generous RSU/Equity package as part of its compensation plan. In addition, we do offer a tremendous benefits plan including employee paid health care, Employee Stock Purchase Plan (ESPP), and other benefits. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive benefits and privileges of employment. Please contact us to request an accommodation. Nearest Major Market: San Jose Nearest Secondary Market: Palo Alto

Fullpower -AI delivers a complete B2B IoT platform for AI-powered algorithms, remote contactless biosensing together with end-to-end engineering services, and customization of software in the field of life sciences, health, and biotechnology. Fullpower's platform is vetted and deployed as a PaaS, backed by a patent portfolio of 135+ patents. Fullpower's key areas of expertise include contactless biosensing, remote monitoring, non-invasive sleep technology, and the development of new technologies for others in the life sciences and biotechnology fields. Fullpower's B2B PaaS customers are in medical solutions, remote-contactless biosensing, bedding solutions, wearable, and wellness services. Fullpower is seeking a passionate, team-oriented, and self-motivated Data Scientist interested in working on our next generation of products and algorithms and modeling rich, biomedical sensor data with a view toward medical, health, and fitness outcomes. The ideal candidate will have a strong background in machine learning and data science and a proven track record of deploying models and algorithms for real-world applications. Job Responsibilities: Work with health data and time-series sensor data Connect biomedical sensor data with medical, health, and fitness outcomes Research and development of machine learning algorithms and statistical models for non-invasive sleep tracking Develop visualizations and tools for understanding and annotating data Optimize algorithms for running on embedded devices and in the cloud Design and run experiments and clinical trials Processing, cleaning, and combining different data sources to create new datasets Collaborate with an interdisciplinary team of scientists, engineers, mathematicians for quick deployment of solutions Software skills: Expertise in Python and packages such as numpy, pandas, scikit-learn Experience with a deep learning framework such as Tensorflow, py Torch, or equivalent Experience working with databases including familiarity with SQL Experience with Amazon Web Services (AWS) or Google Cloud Experience with C++ is a plus Leadership qualities: Self starter Strong interpersonal and communication skills Education and Experience: Experience applying data science and machine learning to real-world problems Bachelor's degree or higher in Mathematics, Statistics, Physics, Computer Science, or equivalent Graduate degree and/or 5+ years experience a plus Additional Information: Fullpower does not sponsor work visas - must already be authorized to work in the United States The base salary range for this full-time position is $130,000 to $170,000, plus equity, plus benefits. Fullpower's salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education and training.

Job DescriptionEstablished in 2017, WeRide (NASDAQ: WRD) is a leading global commercial-stage company that develops autonomous driving technologies from Level 2 to Level 4. WeRide is the only tech company in the world that holds driverless permits in China, the UAE, Singapore and the US, conducting autonomous driving R&D, tests and operations in over 30 cities of 10 countries around the world. WeRide has operated a self-driving fleet for more than 2,200 days. WeRide.ai Silicon Valley team is looking for an experienced and innovative data scientist for its growing metrics team to support the development and validation of both L3+ Advanced Driver Assistance Systems (ADAS) and L4 Autonomous Driving (AD) Systems. The level depends on the candidate's experience and qualification. The metrics team is at the forefront of accelerating the development and deployment of cutting-edge ADAS/AV technologies. As a Senior Data Scientist on this team, you will play a pivotal role in ensuring the safety, reliability, and efficiency of our autonomous systems. You will be responsible for developing and implementing rigorous evaluation frameworks and advanced statistical methodologies to assess overall system performance, as well as the performance of critical sub-systems across software releases, and different territories. Your work will directly inform crucial engineering decisions, guide iterative improvements, and contribute to the successful commercialization of our ADAS/AV stack. What You Will Do: Develop Rigorous Evaluation Frameworks: Design, develop, and implement advanced statistical frameworks for the comprehensive evaluation of ADAS/AV system performance, with a strong emphasis on safety, compliance, and progress metrics. Define and Monitor System Performance: Define, measure, and monitor key performance indicators (KPIs) for the overall ADAS/AV system. Develop automated data pipelines and reporting mechanisms to track these metrics across software releases. Evaluate Sub-system Performance: Define and implement metrics to evaluate the performance of individual sub-systems. Utilize these metrics to provide actionable insights that guide and accelerate sub-system development and improvement. Statistical Analysis and Experimentation: Apply advanced statistical techniques, including hypothesis testing, experimental design, and causal inference, to analyze complex behavioral data and derive robust insights into system performance and regressions between releases. Partner with Engineering Teams: Collaborate closely with Simulation, Systems Engineering, Product, and Software Development teams to integrate evaluation insights into the development lifecycle, inform release readiness, and ensure alignment on performance targets. Technical Leadership and Mentorship: Provide technical leadership on complex data science problems, champion best practices in data analysis and statistical rigor, and mentor junior data scientists within the team. Data Visualization and Communication: Create compelling data visualizations and communicate complex analytical findings clearly and concisely to diverse audiences, ranging from technical engineers to senior leadership. Requirements: Quantitative Degree: Master's degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. Extensive Industry Experience: 3+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. Advanced Statistical Expertise: Deep expertise in advanced statistical methods and their application in real-world settings, including experimental design, hypothesis testing, regression analysis, causal inference and time series analysis, etc. Technical Problem Formulation: Proven ability to translate ambiguous real-world challenges into clearly defined data science problems, identify appropriate methodologies, and deliver effective solutions. Data Manipulation and Analysis: Proficiency in using programming languages (e.g., Python, R) and SQL for data extraction, manipulation, and analysis. Communication: Excellent verbal and written communication skills, with the ability to tailor technical explanations to various stakeholders. Flexibility: Ability to collaborate effectively with teams in different time zones. Preferred Qualifications: PhD degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. 5+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. Experience with large-scale evaluation frameworks for complex software systems, particularly in autonomous driving or robotics. Familiarity with ADAS/AV system architectures and the behavioral challenges inherent in autonomous driving. Knowledge of simulation platforms and their role in data generation and system evaluation. Salary Range: Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $130,000 - $182,000 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. WeRide.ai offers competitive salary depending on the experience. Employee benefits include:Premium Medical, Dental and Vision Plan (No cost from employees or their families) Free Daily Breakfast, Lunch and DinnerPaid vacations and holidays 401K plan We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Established in 2017, WeRide (NASDAQ: WRD) is a leading global commercial-stage company that develops autonomous driving technologies from Level 2 to Level 4. WeRide is the only tech company in the world that holds driverless permits in China, the UAE, Singapore and the US, conducting autonomous driving R&D, tests and operations in over 30 cities of 10 countries around the world. WeRide has operated a self-driving fleet for more than 2,200 days. WeRide.ai Silicon Valley team is looking for an experienced and innovative data scientist for its growing metrics team to support the development and validation of both L3+ Advanced Driver Assistance Systems (ADAS) and L4 Autonomous Driving (AD) Systems. The level depends on the candidate's experience and qualification. The metrics team is at the forefront of accelerating the development and deployment of cutting-edge ADAS/AV technologies. As a Senior Data Scientist on this team, you will play a pivotal role in ensuring the safety, reliability, and efficiency of our autonomous systems. You will be responsible for developing and implementing rigorous evaluation frameworks and advanced statistical methodologies to assess overall system performance, as well as the performance of critical sub-systems across software releases, and different territories. Your work will directly inform crucial engineering decisions, guide iterative improvements, and contribute to the successful commercialization of our ADAS/AV stack. What You Will Do: * Develop Rigorous Evaluation Frameworks: Design, develop, and implement advanced statistical frameworks for the comprehensive evaluation of ADAS/AV system performance, with a strong emphasis on safety, compliance, and progress metrics. * Define and Monitor System Performance: Define, measure, and monitor key performance indicators (KPIs) for the overall ADAS/AV system. Develop automated data pipelines and reporting mechanisms to track these metrics across software releases. * Evaluate Sub-system Performance: Define and implement metrics to evaluate the performance of individual sub-systems. Utilize these metrics to provide actionable insights that guide and accelerate sub-system development and improvement. * Statistical Analysis and Experimentation: Apply advanced statistical techniques, including hypothesis testing, experimental design, and causal inference, to analyze complex behavioral data and derive robust insights into system performance and regressions between releases. * Partner with Engineering Teams: Collaborate closely with Simulation, Systems Engineering, Product, and Software Development teams to integrate evaluation insights into the development lifecycle, inform release readiness, and ensure alignment on performance targets. * Technical Leadership and Mentorship: Provide technical leadership on complex data science problems, champion best practices in data analysis and statistical rigor, and mentor junior data scientists within the team. * Data Visualization and Communication: Create compelling data visualizations and communicate complex analytical findings clearly and concisely to diverse audiences, ranging from technical engineers to senior leadership. Requirements: * Quantitative Degree: Master's degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. * Extensive Industry Experience: 3+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. * Advanced Statistical Expertise: Deep expertise in advanced statistical methods and their application in real-world settings, including experimental design, hypothesis testing, regression analysis, causal inference and time series analysis, etc. * Technical Problem Formulation: Proven ability to translate ambiguous real-world challenges into clearly defined data science problems, identify appropriate methodologies, and deliver effective solutions. * Data Manipulation and Analysis: Proficiency in using programming languages (e.g., Python, R) and SQL for data extraction, manipulation, and analysis. * Communication: Excellent verbal and written communication skills, with the ability to tailor technical explanations to various stakeholders. * Flexibility: Ability to collaborate effectively with teams in different time zones. Preferred Qualifications: * PhD degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. * 5+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. * Experience with large-scale evaluation frameworks for complex software systems, particularly in autonomous driving or robotics. * Familiarity with ADAS/AV system architectures and the behavioral challenges inherent in autonomous driving. * Knowledge of simulation platforms and their role in data generation and system evaluation. Salary Range: Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $130,000 - $182,000 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. WeRide.ai offers competitive salary depending on the experience. Employee benefits include: Premium Medical, Dental and Vision Plan (No cost from employees or their families) Free Daily Breakfast, Lunch and Dinner Paid vacations and holidays 401K plan We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Strategy team. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms preferably in the risk domain. Wed love to chat if you have: Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelors degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience Experience using statistics and data science to solve complex business problems Proficiency in SQL, Python, Excel including key data science libraries Proficiency in data visualization including Tableau Experience working with large datasets Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau. Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact. Desirable to have experience or aptitude solving problems related to risk using data science and analytics Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies Key Job Functions Design rules to detect/mitigate fraud Develop python scripts and models that support strategies Investigate novel/large cases Identify root cause Set strategy for different risk types Work with product/engineering to improvement control capabilities Develop and present strategies and guide execution Expected Outcome in 6-12 months Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that not only solve emerging fraud trends but also provide a great experience to end customers. Utilize data analysis to design and implement fraud strategies Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud solutions that operate at scale and in real time for end customers. Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders. Development of dashboard and visualizations to track KPI of fraud strategies implemented Preferred Skills Data analytics and models Rule development Dashboard Creation Project Management Strong Communication Notes from Hiring Manager: Strong SQL proficiency Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation Proficiency in AWS Quicksight and Tableau Strictly contract to cover multiple leaves over a 1 yr. period. Potential to extend based on business need and performance. Day shift: M-F Pacific time Multiple Zoom interviews (2-3) SQL assessment during 1st interview. MUST HAVE: Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelors degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience. Experience using statistics and data science to solve complex business problems. Experience in SQL, Python, Excel including key data science libraries. Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation. Experience in data visualization including Tableau. Experience working with large datasets.

Did you know that Money Laundering is a primary enabler of criminal activity like drug trafficking, smuggling, terrorism, and corruption around the world with an estimated $2.3 Trillion laundered annually? Criminals are becoming more and more sophisticated in rapidly innovating new ways to launder money and current methods of detecting money laundering are antiquated and ineffective. Quantiply's Sensemaker application suite and platform solutions use AI and machine learning algorithms to identify money laundering and other criminal activities and automatically recommend mitigation strategies and actions. If you are looking for an opportunity to work on complex business problems using the latest AI and Machine Learning technologies, work with best and brightest in crafting innovative solutions while making a positive impact on society, Quantiply is the place for you. Job Description In this role, you will be part of a brand new, trend setting Cognitive Intelligence team which is applying Machine learning and AI to solve complex, business critical problems in the financial services industries. This position within the Cognitive Intelligence team presents a unique and rare opportunity to get in on the ground floor within a fast-growing business and help shape the technology, product, and business. As a real-time transactional intelligence service, our solutions have to be scalable, secure, efficient, and extremely fault-tolerant. A successful candidate will bring: deep technical and software expertise; ability to define visionary, ground breaking products; desire to have an industry-wide impact; and an ability to work within a fast moving, startup environment to rapidly deliver services that drive broad business impact. Responsibilities: Apply your expertise in designing, implementing and validating unsupervised deep learning, reinforcement learning and bayesian models. Present exploratory findings to both, technical and management teams, verbally and in writing. Partner with Product and Engineering teams to explore new opportunities. Engage in collaborating across team members to meet research and product goals. Influence product features and product roadmap through exploratory analysis. Qualifications Minimum qualifications: PhD in machine learning, statistics, engineering, mathematics, computer science, neuroscience, bioinformatics, game theory or other technical field. Strong knowledge of mathematics. Strong knowledge of machine learning and statistics. Strong knowledge of designing algorithms. Some experience in Python and Tensorflow. Preferred qualifications: Strong knowledge of deep learning. Strong knowledge of reinforcement learning. Strong experience in Tensorflow or similar frameworks. Working experience in C++. Additional Information All your information will be kept confidential according to EEO guidelines.

Responsibilities: Work on small and large data sets of structured, semi-structured, and unstructured data to discover hidden knowledge about the client's business and develop methods to leverage that knowledge for their business. Identify and solve business challenges working closely with cross-functional teams, such as Delivery, Business Consulting, Engineering and Product Management. Develop prescriptive and predictive statistical, behavioral or other models via machine learning and/or traditional statistical modeling techniques, and understand which type of model applies best in a given business situation. Drive the collection of new data and the refinement of existing data sources. Analyze and interpret the results of product experiments. Collaborate with the engineering and product teams to develop and support our internal data platform to support ongoing statistical analyses. Qualifications A proven passion for generating insights from data. Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources. Expertise in mathematics and applied statistics, computer science, and visualization capabilities. Curious and an excellent learner. Able to research, explore and acquire working knowledge in new areas. A complete understanding of standard statistical techniques like MLE/QMLE, GMM, OLS/GLS, univariate and multivariate time series models (e.g. ARIMA, DLM's, VAR's), regression model diagnostics for time series and cross sectional data, along with Machine Learning methodologies like Random Forests, SVM's and Boosting/Bagging. The ideal candidate would know when and how to apply these alternative methodologies, and the relative advantages/disadvantages of each for a particular business case. Expert knowledge of an analysis tool/statistical package such as R, JMP, Stata, SPSS, SAS, Matlab Highly effective communicator; able to communicate complex quantitative analysis in a clear, precise & actionable way that is meaningful to general business audience and credible to client's data scientists. Fluency with at least one scripting language such as Python, Java, or C/C++. Expertise with relational databases and SQL. NoSQL is a big plus. REQUIREMENTS: MS or Ph.D. preferred in a quantitative Social Science (e.g. Economics) or Statistics with a substantive field interest. At least 5 years' experience in business, consulting or applied field research with project lead responsibilities for solving analytics problems using quantitative approaches. Demonstrated track record producing models and actionable insights using advanced statistical methods. Experience working with large data sets using distributed computing tools, e.g. Map/Reduce, Hadoop, Hive, etc. Additional Information All your information will be kept confidential according to EEO guidelines.

3MK Software Solutions is the leading software service soltions provider and IT Staffing Supplier company, outsourcing and complex implementation services for the business across different functional areas and technologies with a core focus on software development and web designing development and GIS Software solutions and services. Our team is our core strength, we have selected the most skilled and talented specialists from the IT industry, and we continuously invest in developing their capabilities. The core management has many years of experience and has successfully leaded complex projects for major corporate in the field of healthcare, communication, retail and finance. During the term of these projects, the team had needed to develop an advanced implementation methodology. Job Description JD: We are seeking a smart and engaged Data Scientist to work with our large data sets. As an intelligence connection & search-product oriented firm you can imagine the amount of data we're uncovering . We need your help developing advanced mathematical and statistical models to map data and deliver web analytics. Our product is widely utilized but is perhaps most useful in an academic and / or research capacity. · Natural Language Processing (NLP) , and Machine Learning · Minimum Required Skills: R, Python, SQL, SQL, Hadoop, Algorithms, Machine Learning, Data Mining · Data Scientist - machine learning & NLP modeling · Machine learning development and deployment · advanced NLP modeling · big data framework experience (Spark, MapReduce) · Bachelor's or Master's degree in Computer Science, Statistics, or Mathematics · Develop statistical modeling techniques for pattern recognition problems. · Develop code in Python, R, and SQL, or other object oriented languages for modeling optimization, simulation, and statistical analysis. · Build models that maximize performance and accuracy · Strategic planning and project management. Additional Information All your information will be kept confidential according to EEO guidelines.

Our Employees Are Among The Most Talented People In Their Fields And The Key To Our Success At Samsung, we encourage our employees to showcase their talent through our diverse corporate culture. Our strength is our people. Each individual makes an impact to the company and plays a vital role in contributing to the company's success. Our employees are motivated and passionate. We foster innovative thinking through an enthusiastic work environment. Through synergistic collaboration with other brilliant minds, we build some of the most advanced technology. In order to retain our talented workforce, we provide an excellent benefits package. We encourage a healthy work-life balance so that our employees are satisfied and more productive. We focus on developing our employees by providing them with the right tools and empowering them to succeed. Employee development is a key component of the continuing growth of our business. Our employee development programs help to create a workforce that is well-rounded. Job Description We are seeking a data scientist with at least 1 year of experience working with large data sets and 10 years of total professional experience. This role is expected to translate business objectives into actionable data analysis and communicate findings clearly to technical and non-technical audiences. Qualifications Responsibilities: • Searching for data sets matching data analytics requirements; • Applying transformations to cleanse and shape data set prior to analysis; • Performing exploratory data analysis; • Applying techniques for selecting representative data set features ; • Defining the most suitable machine learning method based on data product requirements; • Applying statistical methods to solve domain problems; • Applying data sampling techniques; • Developing and testing statistical models; • Defining procedures for obtaining data, ensuring validity and accuracy; Collaborating with business units to elicit data analytics requirements; Skills: Required • Analytical thinking; • Understanding of statistics fundamentals; • In-depth knowledge on the Hadoop stack (Map reduce, HDFS, Hive, Pig); • In-depth knowledge on machine learning methods; • Experience with scripting languages such as Python; • Understanding of main statistical methods; • Understanding of sampling techniques; • Understanding of descriptive and inferential statistics concepts; • Business domain experience in one of the following areas: retail, enterprise mobility, healthcare; • B.Sc. degree in Computer Science, Engineering, Mathematics, Statistics or related field is required • M.Sc. degree in related field is desirable. Additional Information Tanya Danylevska Talent acqusition team Samsung SDSA [email protected]

Full-Time | MidSenior Level | No Visa Sponsorship or Relocation A fast-growing financial services organization is seeking a Credit Strategy Data Scientist to join its high-performing Credit Risk Strategy team. This is an exciting opportunity for a data-savvy professional with fintech or payments industry experience to help drive business-critical decisions through advanced analytics, predictive modeling, and risk mitigation strategies. You will work on end-to-end development of data-driven credit solutionspartnering closely with cross-functional stakeholders to design, execute, and refine credit strategies that support responsible growth and customer success. What Youll Do Design and implement data-driven rules to detect and mitigate credit losses Investigate complex and high-impact risk cases and identify root causes Set and refine credit risk strategies across various risk categories Collaborate with product and engineering teams to enhance risk control capabilities Lead the development of dashboards, visualizations, and reports to track credit KPIs Present data-backed recommendations to stakeholders and executives Use large-scale datasets to uncover patterns and drive risk optimization Work with RaaS platforms to analyze loss trends and apply strategic adjustments Must-Have Qualifications Bachelors degree in Computer Science, Engineering, Mathematics, Statistics, Data Mining, or a related field (or equivalent practical experience) 2+ years of hands-on experience in risk analytics, data science, or data analysispreferably within fintech or online payments Proficiency in SQL, Python, and Excel, including core data science libraries Proven ability to work with large datasets and derive actionable insights Experience developing and communicating dashboards and visualizations (e.g. Tableau) Strong communication skills and ability to translate complex analysis to diverse audiences Demonstrated data-driven decision-making and solution development Preferred Skills & Experience Experience applying data science to credit risk and loss mitigation problems Familiarity with AWS, payment rule systems, or credit product lifecycles Strong project management skills and ability to drive analytics from concept to execution Comfortable working in fast-paced, ambiguous environments with shifting priorities Expected Outcomes (6-12 Months) Design and deployment of credit strategies based on emerging loss trends Creation of performance dashboards and tools to monitor KPIs and credit risk health Collaboration with product and engineering teams to implement real-time credit decisioning Delivery of presentations and reports to support strategic decisions at all levels Key Competencies Data Analytics & Visualization Credit Rule Development Strategic Communication Cross-Functional Collaboration Project Ownership & Execution Interview Process At-home screening assignment Technical interview with senior team member Final panel interview with hiring manager and team Team Size: 5 members Work Style: Close collaboration with senior data scientists initially, with room for independent ownership over time. Focus Area: Reporting, visualization, and strategy design This is a high-impact role at the intersection of data science, risk management, and business strategyperfect for professionals passionate about leveraging data to drive innovation in financial services. Apply now to help shape the future of responsible credit risk management.

Fraud Strategy Data Scientist, Risk Data Scientist w/Fraud, Risk Analytics, Data Analysis, Data Science, Fraud Mitigation, Industry: eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse, SQL, Tableau, Data Science Libraries Experience level: Mid-senior Experience required: 3 Years Education level: Bachelor's degree Job function: Finance Industry: Financial Services Pay rate : View hourly payrate Total position: 1 Relocation assistance: No Visa sponsorship eligibility: No Note: This is a hybrid position, so candidates must be based in the San Jose area. JOB DESCRIPTION: We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Strategy team. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation at Bill.com. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms preferably in the risk domain. We'd love to chat if you have: Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelor's degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience Experience using statistics and data science to solve complex business problems Proficiency in SQL, Python, Excel including key data science libraries Proficiency in data visualization including Tableau Experience working with large datasets Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau. Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact. Desirable to have experience or aptitude solving problems related to risk using data science and analytics Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies Key Job Functions Design rules to detect/mitigate fraud Develop python scripts and models that support strategies Investigate novel/large cases Identify root cause Set strategy for different risk types Work with product/engineering to improvement control capabilities Develop and present strategies and guide execution Expected Outcome in 6-12 months Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that not only solve emerging fraud trends but also provide a great experience to end customers. Utilize data analysis to design and implement fraud strategies Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud solutions that operate at scale and in real time for end customers. Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders. Development of dashboard and visualizations to track KPI of fraud strategies implemented Preferred Skills Data analytics and models Rule development Dashboard Creation Project Management Strong Communication Notes from Hiring Manager: Strong SQL proficiency Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation Proficiency in AWS Quicksight and Tableau Strictly contract to cover multiple leaves over a 1 yr. period. Potential to extend based on business need and performance. Day shift: M-F Pacific time Multiple Zoom interviews (2-3) - SQL assessment during 1st interview. MUST HAVE: Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelor's degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience. Experience using statistics and data science to solve complex business problems. Experience in SQL, Python, Excel including key data science libraries. Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation. Experience in data visualization including Tableau. Experience working with large datasets.

We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Strategy team. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation at Bill.com. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms preferably in the risk domain. Wed love to chat if you have: Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelors degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience Experience using statistics and data science to solve complex business problems Proficiency in SQL, Python, Excel including key data science libraries Proficiency in data visualization including Tableau Experience working with large datasets Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau. Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact. Desirable to have experience or aptitude solving problems related to risk using data science and analytics Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies Key Job Functions Design rules to detect/mitigate fraud Develop python scripts and models that support strategies Investigate novel/large cases Identify root cause Set strategy for different risk types Work with product/engineering to improvement control capabilities Develop and present strategies and guide execution Expected Outcome in 6-12 months Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that not only solve emerging fraud trends but also provide a great experience to end customers. Utilize data analysis to design and implement fraud strategies Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud solutions that operate at scale and in real time for end customers. Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders. Development of dashboard and visualizations to track KPI of fraud strategies implemented Preferred Skills Data analytics and models Rule development Dashboard Creation Project Management Strong Communication Notes from Hiring Manager: Strong SQL proficiency Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation Proficiency in AWS Quicksight and Tableau Strictly contract to cover multiple leaves over a 1 yr. period. Potential to extend based on business need and performance. Day shift: M-F Pacific time Multiple Zoom interviews (2-3) SQL assessment during 1st interview. MUST HAVE: Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelors degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience. Experience using statistics and data science to solve complex business problems. Experience in SQL, Python, Excel including key data science libraries. Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation. Experience in data visualization including Tableau. Experience working with large datasets.

Our Employees Are Among The Most Talented People In Their Fields And The Key To Our Success At Samsung, we encourage our employees to showcase their talent through our diverse corporate culture. Our strength is our people. Each individual makes an impact to the company and plays a vital role in contributing to the company's success. Our employees are motivated and passionate. We foster innovative thinking through an enthusiastic work environment. Through synergistic collaboration with other brilliant minds, we build some of the most advanced technology. In order to retain our talented workforce, we provide an excellent benefits package. We encourage a healthy work-life balance so that our employees are satisfied and more productive. We focus on developing our employees by providing them with the right tools and empowering them to succeed. Employee development is a key component of the continuing growth of our business. Our employee development programs help to create a workforce that is well-rounded. Job Description We are seeking a data scientist with at least 1 year of experience working with large data sets and 10 years of total professional experience. This role is expected to translate business objectives into actionable data analysis and communicate findings clearly to technical and non-technical audiences. Qualifications Responsibilities: • Searching for data sets matching data analytics requirements; • Applying transformations to cleanse and shape data set prior to analysis; • Performing exploratory data analysis; • Applying techniques for selecting representative data set features ; • Defining the most suitable machine learning method based on data product requirements; • Applying statistical methods to solve domain problems; • Applying data sampling techniques; • Developing and testing statistical models; • Defining procedures for obtaining data, ensuring validity and accuracy; Collaborating with business units to elicit data analytics requirements; Skills: Required • Analytical thinking; • Understanding of statistics fundamentals; • In-depth knowledge on the Hadoop stack (Map reduce, HDFS, Hive, Pig); • In-depth knowledge on machine learning methods; • Experience with scripting languages such as Python; • Understanding of main statistical methods; • Understanding of sampling techniques; • Understanding of descriptive and inferential statistics concepts; • Business domain experience in one of the following areas: retail, enterprise mobility, healthcare; • B.Sc. degree in Computer Science, Engineering, Mathematics, Statistics or related field is required • M.Sc. degree in related field is desirable. Additional Information Tanya Danylevska Talent acqusition team Samsung SDSA [email protected]