Data scientist jobs in Hayward, CA - 2,778 jobs

A leading global consulting firm seeks a Data Scientist - Director in San Francisco to drive AI solutions and data initiatives. The ideal candidate will lead multi-source data pipelines, architect complex data solutions while collaborating with business leaders. Candidates should have a strong educational background, extensive experience in data engineering, and proficiency with SQL and cloud-native infrastructure. This role offers a competitive salary range of $205,000 to $235,000 and promotes a hybrid working model. #J-18808-Ljbffr

A leading technology company seeks a Senior Product Data Scientist in Mountain View, CA, to analyze data and provide strategic insights to enhance product decisions. Candidates should have a bachelor's in a quantitative field, with 8 years of experience in analytics, coding skills in Python, R, and SQL, and a passion for problem-solving. This role offers a competitive salary range of $156,000 to $229,000, along with a bonus, equity, and benefits. #J-18808-Ljbffr

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel. About the Role As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth. Key Responsibilities Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections. Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives. Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects. Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions. Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting. Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations. About You Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments. Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions. Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy. Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams. Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.

At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Gilead's AI Research Center(ARC) is looking for a Principal Data Scientist to spearhead the adoption of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide key thought leadership and drive our strategic vision for advanced analytics, with the goal of optimizing clinical trials, enhancing data-driven decision-making, and providing support for Real-World Evidence (RWE), Clinical Pharmacology, and Biomarkers initiatives. You will be a thought leader in applying AI/ML to real-world clinical challenges, taking deep involvement in all stages of technical development-from coding and configuring compute environments to model evaluation, review, and architecture design. You'll work closely with a variety of cross-functional teams, including architects, data engineers, and product managers, to scope, develop, and operationalize our AI-driven applications, with a specific focus on leveraging AI/ML to advance insights within RWE, Clinical Pharmacology, and Biomarkers. Responsibilities: Innovate and Strategize: Spearhead the strategic vision for leveraging AI/ML within clinical development. You'll partner with cross-functional leaders to identify high-impact opportunities and design innovative solutions that transform how we conduct trials and make data-driven decisions. Lead with Expertise: Guide the full lifecycle of machine learning models from initial concept to real-world application. This includes architecting scalable solutions, hands-on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers. Mentor and Empower: Act as a force multiplier for our data science team. You'll coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning. Translate and Execute: Serve as a bridge between technical teams and business stakeholders. You'll translate complex business challenges into precise data science problems and, in a product manager-like role, drive the development of these solutions from proof-of-concept to production. Drive Breakthroughs: Research and develop cutting-edge algorithms to solve critical challenges. This could involve using NLP for patient insights, computer vision for biomarker analysis, or predictive models to optimize trial logistics. You'll be at the forefront of applying these techniques in a biotech context. Build the Foundation: Design and implement the technical and process building blocks needed to scale our AI/ML capabilities. This includes working with IT partners to curate and operationalize the datasets essential for fueling our analytical pipelines. Influence and Advise: Interface directly with internal stakeholders, acting as a trusted advisor to help them understand the potential of advanced analytics and apply data-driven approaches to optimize clinical trial operations. Stay Ahead: Continuously monitor the landscape of machine learning and biopharmaceutical innovation. You'll ensure our team is leveraging the latest state-of-the-art techniques to maintain a competitive edge. Technical Skills: Advanced Model Development & Operationalization: Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale. This includes a profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes. Data & Computational Proficiency: Fluent in Python or R and SQL, with hands-on experience in building and optimizing data pipelines for analytical and model development purposes. Cloud-Native AI/ML: Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring. Translational Research: Proven ability to translate foundational AI/ML research into functional, production-ready packages and applications that directly support strategic initiatives in areas like RWE, Clinical Pharmacology, and Biomarkers. Basic Qualifications: Doctorate and 5+ years of relevant experience OR Master's and 8+ years of relevant experience OR Bachelor's and 10+ years of relevant experience Preferred Qualifications: Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers. Skill in scoping project requirements and developing timelines. Knowledge of product management principles. Experience with code management using Git. Strong technical documentation skills. Join us at the AI Research Center to shape the future of clinical development with groundbreaking AI/ML solutions, and contribute to advancements in RWE, Clinical Pharmacology, and Biomarkers! The salary range for this position is: Bay Area: $210,375.00 - $272,250.00.Other US Locations: $191,250.00 - $247,500.00. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description Gilead's AI Research Center(ARC) is looking for a Principal Data Scientist to spearhead the adoption of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide key thought leadership and drive our strategic vision for advanced analytics, with the goal of optimizing clinical trials, enhancing data-driven decision-making, and providing support for Real-World Evidence (RWE), Clinical Pharmacology, and Biomarkers initiatives. You will be a thought leader in applying AI/ML to real-world clinical challenges, taking deep involvement in all stages of technical development-from coding and configuring compute environments to model evaluation, review, and architecture design. You'll work closely with a variety of cross-functional teams, including architects, data engineers, and product managers, to scope, develop, and operationalize our AI-driven applications, with a specific focus on leveraging AI/ML to advance insights within RWE, Clinical Pharmacology, and Biomarkers. Responsibilities: Innovate and Strategize: Spearhead the strategic vision for leveraging AI/ML within clinical development. You'll partner with cross-functional leaders to identify high-impact opportunities and design innovative solutions that transform how we conduct trials and make data-driven decisions. Lead with Expertise: Guide the full lifecycle of machine learning models from initial concept to real-world application. This includes architecting scalable solutions, hands-on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers. Mentor and Empower: Act as a force multiplier for our data science team. You'll coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning. Translate and Execute: Serve as a bridge between technical teams and business stakeholders. You'll translate complex business challenges into precise data science problems and, in a product manager-like role, drive the development of these solutions from proof-of-concept to production. Drive Breakthroughs: Research and develop cutting-edge algorithms to solve critical challenges. This could involve using NLP for patient insights, computer vision for biomarker analysis, or predictive models to optimize trial logistics. You'll be at the forefront of applying these techniques in a biotech context. Build the Foundation: Design and implement the technical and process building blocks needed to scale our AI/ML capabilities. This includes working with IT partners to curate and operationalize the datasets essential for fueling our analytical pipelines. Influence and Advise: Interface directly with internal stakeholders, acting as a trusted advisor to help them understand the potential of advanced analytics and apply data-driven approaches to optimize clinical trial operations. Stay Ahead: Continuously monitor the landscape of machine learning and biopharmaceutical innovation. You'll ensure our team is leveraging the latest state-of-the-art techniques to maintain a competitive edge. Technical Skills: Advanced Model Development & Operationalization: Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale. This includes a profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes. Data & Computational Proficiency: Fluent in Python or R and SQL, with hands-on experience in building and optimizing data pipelines for analytical and model development purposes. Cloud-Native AI/ML: Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring. Translational Research: Proven ability to translate foundational AI/ML research into functional, production-ready packages and applications that directly support strategic initiatives in areas like RWE, Clinical Pharmacology, and Biomarkers. Basic Qualifications: Doctorate and 5+ years of relevant experience OR Master's and 8+ years of relevant experience OR Bachelor's and 10+ years of relevant experience Preferred Qualifications: Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers. Skill in scoping project requirements and developing timelines. Knowledge of product management principles. Experience with code management using Git. Strong technical documentation skills. Join us at the AI Research Center to shape the future of clinical development with groundbreaking AI/ML solutions, and contribute to advancements in RWE, Clinical Pharmacology, and Biomarkers! The salary range for this position is: Bay Area: $210,375.00 - $272,250.00.Other US Locations: $191,250.00 - $247,500.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans*. For additional benefits information, visit: ****************************************************************** * Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans. For jobs in the United States: Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex , age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact ApplicantAccommodations@gilead.com for assistance. For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster. NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT PAY TRANSPARENCY NONDISCRIMINATION PROVISION Our environment respects individual differences and recognizes each employee as an integral member of our company. Our workforce reflects these values and celebrates the individuals who make up our growing team. Gilead provides a work environment free of harassment and prohibited conduct. We promote and support individual differences and diversity of thoughts and opinion. For Current Gilead Employees and Contractors: Please apply via the Internal Career Opportunities portal in Workday. Share: Job Requisition ID R0046852 Full Time/Part Time Full-Time Job Level Associate Director Click below to return to the Gilead Careers site Click below to see a list of upcoming events Click below to return to the Kite, a Gilead company Careers site #J-18808-Ljbffr

Data Scientist Everfit | Hybrid, San Francisco Bay Area Everfit is a fitness technology company building an AI-powered coaching platform that serves 280,000+ coaches and Millions of training clients globally. We're transforming how fitness professionals deliver personalized training and nutrition guidance to their clients through intelligent automation and data-driven insights. About the Role We're looking for a senior data scientist who is passionate about fitness and energized by turning data into actionable insights that help coaches and their clients succeed. You'll play a critical role in understanding user behavior, product performance, and business metrics to inform strategic decisions as we scale our platform. What You'll Do Product Analytics & User Insights Define and track key product metrics (activation, engagement, retention, churn) to measure product health and success. Conduct cohort, funnel, and retention analyses to uncover behavioral insights and inform feature prioritization. Identify opportunities to improve onboarding, engagement, and coach-client interactions. Experimentation & A/B Testing Own the experimentation framework and guide teams through hypothesis design, sample sizing, execution, and interpretation. Strategic Impact & Roadmapping Collaborate with leadership to translate data insights into roadmap priorities and measurable business outcomes. Build predictive models and scenario analyses to support forecasting, pricing, and product investment decisions. Establish best practices in data instrumentation, dashboarding, and self-serve analytics across teams. Technical Foundations Partner with data engineering to improve pipelines and instrumentation. Leverage tools such as SQL, Python/R, data visualization platforms, and experimentation platforms. Marketing Analytics & Optimization Analyze customer acquisition funnels and marketing performance to identify high-impact opportunities for growth and conversion. Partner with marketing and growth teams to design and evaluate campaign experiments What We're Looking For 4-6 years of experience in a data analyst or analytics role, preferably at a growth-stage tech company Strong proficiency in SQL and experience setting up data pipelines, transforming data, and analyzing large datasets Deep experience with creating dashboards and providing analysis on product analytics and data visualization tools (Amplitude, Looker, Tableau, Mode, or similar) Understanding of SaaS metrics and cohort analysis Experience with translating numerical findings into clear insights for non-technical team members Genuine passion for fitness, health, or wellness (we build for coaches so you need to understand their world) Bonus Points: Experience with Python or R for statistical analysis Experience in a PLG (Product-Led Growth) environment Experience working at a company during a hypergrowth phase Background in fitness, health, wellness, or coaching industries You'll thrive here if you: Are naturally curious and love asking "why" until you find the answer Are excited by fast-paced, high-growth environments with a passion for building out systems for scaling Enjoy collaborating with global teams and making complex topics understandable Are comfortable with ambiguity and can structure your own work Care deeply about the impact your insights have on real coaches and their clients Why Join Everfit Establish the foundations for Fitness Intelligence and help shape the future of coaching for millions around the world Work with autonomy and ownership on high-impact projects Join a collaborative, global team with experience from leading tech and fitness companies Enjoy competitive salary, equity, and performance bonuses Build something meaningful that helps people live better, healthier lives Everfit is an equal opportunity employer committed to building a diverse and inclusive team. We make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected status. Ready to dive into data in the fitness intelligence space? We'd love to hear from you.

Data Scientist - Machine Learning and AI Team Duration: Full-Time, Permanent Salary: $175k - $225k We are seeking a Data Scientist to join our Machine Learning team. You will work on data-driven projects, from exploratory analysis to building and deploying ML models for security and networking use cases. This role involves close collaboration with cross-functional teams to deliver actionable insights and scalable solutions. Key Responsibilities Data Analysis & Visualization: Perform EDA and communicate insights using visualization tools. Data Engineering: Ingest, clean, preprocess, and label datasets for modeling. Machine Learning: Develop and evaluate models for threat/vulnerability detection using CNNs, LSTM, DNNs, and advanced NLP/Vision models (Transformers, Mamba). Model Deployment: Collaborate with engineering for production deployment; experience with quantization, evaluation, and formats like ONNX, GGUF. Optimization: Improve training pipelines and inference performance. Collaboration: Work with data engineers, analysts, and domain experts to translate business needs into ML solutions. Qualifications Master's degree in Computer Science/Engineering. 4-5 years of experience in data science or related field. Strong Python skills; experience with Pandas/Polars, NumPy, Matplotlib, Seaborn. Knowledge of ML algorithms and deep learning frameworks (TensorFlow, PyTorch). Familiarity with NLP and LLMs is a plus. Excellent problem-solving and communication skills. Preferred: Experience with Go/Rust. Neural Networks Background in threat modeling, anomaly detection. Distributed training (RAPIDS, Dask, Ray). Cloud platforms (AWS, GCP, Azure). MLOps tools (MLFlow, ClearML); DevOps (Docker, K8s, Helm, Terraform).

Sunnyvale, California, United States Machine Learning and AI The Video Computer Vision organization is working on exciting technologies for future Apple products. Our team delivers computer vision and machine learning algorithms that power many Apple technologies human understanding and human intelligence algorithms with applications for digital humans, health and AI. In this role, you will work closely with our team of experts in computer graphics, computer vision and machine learning to develop and extend pipeline infrastructure used for solving large-scale data challenges, to help deliver new algorithms for Apple products and bring high impact to millions of users. Description Join us as an ML Data and Infrastructure Engineer and become the architect behind the data infrastructure that power tomorrow's breakthrough AI/ML innovations. You'll be the critical link between ambitious algorithmic vision and real-world implementation-building the robust, scalable infrastructure that turns cutting-edge research into production-ready systems. We don't just use tools; we build them. You'll have complete ownership of the infrastructure that fuels our ML algorithms from conception to deployment, designing and orchestrating distributed compute systems that process massive datasets at scales few engineers ever encounter. Working shoulder-to-shoulder with AI/ML researchers and engineers in a small, agile team, you'll drive the creation of scalable infrastructure for ground truth data delivery, orchestrate massive distributed compute tasks across petabyte-scale datasets, develop novel validation frameworks, and help define strategic data collection approaches that push the boundaries of what's achievable. Your contributions won't just support algorithms-they'll directly shape product direction, unlock entirely new AI/ML capabilities, and define what's possible at Apple. Minimum Qualifications BS in computer science or related discipline and 3+ years of relevant industry experience. Experience developing or extending frameworks used for automating pipelines. Strong software engineering skills with extensive experience in Python. Strong foundational knowledge in Computer Science, with a deep understanding of algorithms and data structures. Preferred Qualifications MS or PhD computer science or related discipline, or 5+ years of related industry experience. Experience processing large, complex, unstructured data. Experience developing core infrastructure and frameworks for automating data pipelines. Excellent communication and experience working with multi-functional teams. Passion for delivering high quality software to end-users. Experience with geometry or computer vision algorithms. Self-motivated, with an ability to drive projects from concept to production, balancing requirements with technical quality and development timelines. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . Apple accepts applications to this posting on an ongoing basis. #J-18808-Ljbffr

Job Description - Senior Applications Consultant - Workday Data Consultant (054374) Senior Applications Consultant - Workday Data Consultant Qualifications & Experience: Certified in Workday HCM Experience in Workday data conversion At least one implementation as a data consultant Ability to work with clients on data conversion requirements and load data into Workday tenants Flexible to work across delivery landscape including Agile Applications Development, Support, and Deployment Valid US work authorization (no visa sponsorship required) 6‑8 years overall experience (minimum 2 years relevant), Bachelor's degree SE Level 1 certification; pursuing Level 2 Experience in package configuration, business analysis, architecture knowledge, technical solution design, vendor management Responsibilities: Translate business cases into detailed technical designs Manage operational and technical issues, translating blueprints into requirements and specifications Lead integration testing and user acceptance testing Act as stream lead guiding team members Participate as an active member within technology communities Capgemini is an Equal Opportunity Employer encouraging diversity and providing accommodations for disabilities. All qualified applicants will receive consideration without regard to race, national origin, gender identity or expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status, or any other characteristic protected by law. Physical, mental, or environmental demands may be referenced. Reasonable accommodations will be considered where possible. #J-18808-Ljbffr

Are you an experienced Data Scientist with a desire to excel? If so, then Talent Software Services may have the job for you! Our client is seeking an experienced Data Scientist to work at their company in Novato, CA. Client's Data Science is responsible for designing, capturing, analyzing, and presenting data that can drive key decisions for Clinical Development, Medical Affairs, and other business areas of Client. With a quality-by-design culture, Data Science builds quality data that is fit-for-purpose to support statistically sound investigation of critical scientific questions. The Data Science team develops solid analytics that are visually relevant and impactful in supporting key data-driven decisions across Client. The Data Management Science (DMS) group contributes to Data Science by providing complete, correct, and consistent analyzable data at data, data structure and documentation levels following international standards and GCP. The DMS Center of Risk Based Quality Management (RBQM) sub-function is responsible for the implementation of a comprehensive, cross-functional strategy to proactively manage quality risks for clinical trials. Starting at protocol development, the team collaborates to define critical-to-quality factors, design fit-for-purpose quality strategies, and enable ongoing oversight through centralized monitoring and data-driven risk management. The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined KRIs, QTLs, and other risk metrics using clinical data, with strong emphasis on SAS programming to deliver robust and scalable analytics across multiple studies. Primary Responsibilities/Accountabilities: The RBQM Data Scientist may perform a range of the following responsibilities, depending upon the study's complexity and the study's development stage: Implement and maintain pre-defined KRIs, QTLs, and triggers using robust SAS programs/macros across multiple clinical studies. Extract, transform, and integrate data from EDC systems (e.g., RAVE) and other clinical sources into analysis-ready SAS datasets. Run routine and ad-hoc RBQM/central monitoring outputs (tables, listings, data extracts, dashboard feeds) to support signal detection and study review. Perform QC and troubleshooting of SAS code; ensure outputs are accurate and efficient. Maintain clear technical documentation (specifications, validation records, change logs) for all RBQM programs and processes. Collaborate with Central Monitors, Central Statistical Monitors, Data Management, Biostatistics, and Study Operations to understand requirements and ensure correct implementation of RBQM metrics. Qualifications: PhD, MS, or BA/BS in statistics, biostatistics, computer science, data science, life science, or a related field. Relevant clinical development experience (programming, RBM/RBQM, Data Management), for example: PhD: 3+ years MS: 5+ years BA/BS: 8+ years Advanced SAS programming skills (hard requirement) in a clinical trials environment (Base SAS, Macro, SAS SQL; experience with large, complex clinical datasets). Hands-on experience working with clinical trial data.•Proficiency with Microsoft Word, Excel, and PowerPoint. Technical - Preferred / Strong Plus Experience with RAVE EDC. Awareness or working knowledge of CDISC, CDASH, SDTM standards. Exposure to R, Python, or JavaScript and/or clinical data visualization tools/platforms. Preferred: Knowledge of GCP, ICH, FDA guidance related to clinical trials and risk-based monitoring. Strong analytical and problem-solving skills; ability to interpret complex data and risk outputs. Effective communication and teamwork skills; comfortable collaborating with cross-functional, global teams. Ability to manage multiple programming tasks and deliver high-quality work in a fast-paced environment.

A cutting-edge data analytics firm in San Francisco is seeking a full-stack engineer to enhance user experiences and integrate AI tools within their platform. You will work on innovative projects that shape data interactions, collaborate with teams on product initiatives, and tackle UX challenges. Ideal candidates should possess 3+ years of software engineering experience, proficiency in React and Typescript, and a strong desire to work in AI development. This position offers a competitive salary and benefits, with a hybrid work model. #J-18808-Ljbffr

Zyphra is an artificial intelligence company based in Palo Alto, California. The Role: As a Machine Learning Data Engineer - Systems & Retrieval, you will build and optimize the data infrastructure that fuels our machine learning systems. This includes designing high-performance pipelines for collecting, transforming, indexing, and serving massive, heterogeneous datasets from raw web-scale data to enterprise document corpora. You'll play a central role in architecting retrieval systems for LLMs and enabling scalable training and inference with clean, accessible, and secure data. You'll have an impact across both research and product teams by shaping the foundation upon which intelligent systems are trained, retrieved, and reasoned over. You'll work across: Design and implementation of distributed data ingestion and transformation pipelines Building retrieval and indexing systems that support RAG and other LLM-based methods Mining and organizing large unstructured datasets, both in research and production environments Collaborating with ML engineers, systems engineers, and DevOps to scale pipelines and observability Ensuring compliance and access control in data handling, with security and auditability in mind Requirements: Strong software engineering background with fluency in Python Experience designing, building, and maintaining data pipelines in production environments Deep understanding of data structures, storage formats, and distributed data systems Familiarity with indexing and retrieval techniques for large-scale document corpora Understanding of database systems (SQL and NoSQL), their internals, and performance characteristics Strong attention to security, access controls, and compliance best practices (e.g., GDPR, SOC2) Excellent debugging, observability, and logging practices to support reliability at scale Strong communication skills and experience collaborating across ML, infra, and product teams Bonus Skill Set: Experience building or maintaining LLM-integrated retrieval systems (e.g, RAG pipelines) Academic or industry background in data mining, search, recommendation systems, or IR literature Experience with large-scale ETL systems and tools like Apache Beam, Spark, or similar Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding-based retrieval Understanding of data validation and quality assurance in machine learning workflows Experience working on cross-functional infra and MLOps teams Knowledge of how data infrastructure supports training pipelines, inference serving, and feedback loops Comfort working across raw, unstructured data, structured databases, and model-ready formats Why Work at Zyphra: Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued We strongly value new and crazy ideas and are very willing to bet big on new ideas We move as quickly as we can; we aim to minimize the bar to impact as low as possible We all enjoy what we do and love discussing AI Benefits and Perks: Comprehensive medical, dental, vision, and FSA plans Competitive compensation and 401(k) Relocation and immigration support on a case-by-case basis On-site meals prepared by a dedicated culinary team; Thursday Happy Hours In-person team in Palo Alto, CA, with a collaborative, high-energy environment If you're excited by the challenge of high-scale, high-performance data engineering in the context of cutting-edge AI, you'll thrive in this role. Apply Today! #J-18808-Ljbffr

About us At Eon, we are at the forefront of large-scale neuroscientific data collection. Our mission is to enable the safe and scalable development of brain emulation technology to empower humanity over the next decade, beginning with the creation of a fully emulated digital twin of a mouse. Role We're a San Francisco team collecting very large microscopy datasets and we need an expert to design and implement our end-to-end data pipeline, from high-rate ingest to multi-petabyte storage and downstream processing. You'll own the strategy (on-prem vs. S3 or hybrid), the bill of materials, and the deployment, and you'll be on the floor wiring, racking, tuning, and validating performance. Our current instruments generate data at ~1+ GB/s sustained (higher during bursts) and the program will accumulate multiple petabyes total over time. You'll help us choose and implement the right architecture considering reliability and cost controls. Outcomes (what success looks like) Within 2 weeks: Implement an immediate data-handling strategy that reliably ingests our initial data streams. Within 2 weeks: Deliver a documented medium-term data architecture covering storage, networking, ingest, and durability. Within 1 month: Operationalize the medium-term pipeline in production (ingest → buffer → long-term store → compute access). Ongoing: Maintain ≥95% uptime for the end-to-end data-handling pipeline after setup. Responsibilities Architect ingest & storage: Choose and implement an on-prem hardware and data pipeline design or a cloud/S3 alternative with explicit cost and performance tradeoffs at multi-petabyte scale. Set up a sustained-write ingest path ≥1 GB/s with adequate burst headroom (camera/frame-to-disk), including networking considerations, cooling, and throttling safeguards. Optimize footprint & cost: Incorporate on-the-fly compression/downsampling options and quantify CPU budget vs. write-speed tradeoffs; document when/where to compress to control $/PB. Integrate with acquisition workflows ensuring image data and metadata are compatible with downstream stitching/flat-field correction pipelines. Enable downstream compute: Expose the data to segmentation/analysis stacks (local GPU nodes or cloud). Skills 5+ years designing and deploying high-throughput storage or HPC pipelines (≥1 GB/s sustained ingest) in production. Deep hands-on with: NVMe RAID/striping, ZFS/MDRAID/erasure coding, PCIe topology, NUMA pinning, Linux performance tuning, and NIC offload features. Proven delivery of multi-GB/s ingest systems and petabyte-scale storage in production (life-sciences, vision, HPC, or media). Experience building tiered storage systems (NVMe → HDD/object) and validating real-world throughput under sustained load. Practical S3/object-storage know-how (AWS S3 and/or on-prem S3-compatible systems) with lifecycle, versioning, and cost controls. Data integrity & reliability: snapshots, scrubs, replication, erasure coding, and backup/DR for PB-scale systems. Networking: ****25/40/100 GbE (SFP+/SFP28), RDMA/ RoCE/iWARP familiarity; switch config and path tuning. Ability to spec and rack hardware: selecting chassis/backplanes, RAID/HBA cards, NICs, and cooling strategies to prevent NVMe throttling under sustained writes. Ideal skills: Experience with microscopy or scientific imaging ingest at frame-to-disk speeds, including Micro-Manager-based pipelines and raw-to-containerized format conversions. Experience with life science imaging data a plus. Engagement details Contract (1099 or corp-to-corp); contract-to-hire if there's a mutual fit. On-site requirement: You must be physically present in San Francisco during build-out and initial operations; local field work (e.g., UCSF) as needed. Compensation: Contract, $100-300/hour Timeline: Immediate start #J-18808-Ljbffr

Mechanical design, the work done in CAD, is the rate-limiter for progress in the physical world. However, there are only 2-4 million people on Earth who know how to CAD. But what if hundreds of millions could? What if creating something in the real world were as easy as imagining the use case, or sketching it on paper? Backflip is building a foundation model for mechanical design: unifying the world's scattered engineering knowledge into an intelligent, end-to-end design environment. Our goal is to enable anyone to imagine a solution and hit “print.” Founded by a second-time CEO in the same space (first company: Markforged), Backflip combines deep industry insight with breakthrough AI research. Backed by a16z and NEA, we raised a $30M Series A and built a deeply technical, mission-driven team. We're building the AI foundation that tomorrow's space elevators, nanobots, and spaceships will be built in. If you're excited to define the next generation of hard tech, come build it with us. The Role We're looking for a Staff Machine Learning Data Engineer to lead and build the data pipelines powering Backflip's foundation model for manufacturing and CAD. You'll design the systems, tools, and strategies that turn the world's engineering knowledge - text, geometry, and design intent - into high-quality training data. This is a core leadership role within the AI team, driving the data architecture, augmentation, and evaluation that underpin our model's performance and evolution. You'll collaborate with Machine Learning Engineers to run data-driven experiments, analyze results, and deliver AI products that shape the future of the physical world. What You'll Do Architect and own Backflip's ML data pipeline, from ingestion to processing to evaluation. Define data strategy: establish best practices for data augmentation, filtering, and sampling at scale. Design scalable data systems for multimodal training (text, geometry, CAD, and more). Develop and automate data collection, curation, and validation workflows. Collaborate with MLEs to design and execute experiments that measure and improve model performance. Build tools and metrics for dataset analysis, monitoring, and quality assurance. Contribute to model development through insights grounded in data, shaping what, how, and when we train. Who You Are You've built and maintained ML data pipelines at scale, ideally for foundation or generative models, that shipped into production in the real world. You have deep experience with data engineering for ML, including distributed systems, data extraction, transformation, and loading, and large-scale data processing (e.g. PySpark, Beam, Ray, or similar). You're fluent in Python and experienced with ML frameworks and data formats (Parquet, TFRecord, HuggingFace datasets, etc.). You've developed data augmentation, sampling, or curation strategies that improved model performance. You think like both an engineer and an experimentalist: curious, analytical, and grounded in evidence. You collaborate well across AI development, infra, and product, and enjoy building the data systems that make great models possible. You care deeply about data quality, reproducibility, and scalability. You're excited to help shape the future of AI for physical design. Bonus points if: You are comfortable working with a variety of complex data formats, e.g. for 3D geometry kernels or rendering engines. You have an interest in math, geometry, topology, rendering, or computational geometry. You've worked in 3D printing, CAD, or computer graphics domains. Why Backflip This is a rare opportunity to own the data backbone of a frontier foundation model, and help define how AI learns to design the physical world. You'll join a world-class, mission-driven team operating at the intersection of research, engineering, and deep product sense, building systems that let people design the physical world as easily as they imagine it. Your work will directly shape the performance, capability, and impact of Backflip's foundation model, the core of how the world will build in the future. Let's build the tools the future will be made in. #J-18808-Ljbffr

A data consulting firm based in San Francisco is seeking a Palantir Foundry Consultant for a contract position. The ideal candidate should have strong experience in Palantir Foundry, SQL, and PySpark, with proven skills in data pipeline development and ETL automation. Responsibilities include building data pipelines, implementing interactive dashboards, and leveraging data analysis for actionable insights. This on-site role offers an excellent opportunity for those experienced in the field. #J-18808-Ljbffr

Role: Lead Data Engineer - Future of Email POD (MarTech Engineering & Orchestration) Key Skills: Scala, Databricks, Spark SQL, Spark Streaming, MarTech and Orchestration. Experience : 10+ years Mode: Hybrid We're at Coforge is seeking for Lead Engineer in the FOE POD is a senior technical leader responsible for architecting, building, and scaling next‑generation marketing technology solutions. This role blends deep MarTech orchestration expertise with modern big‑data engineering, cloud-native design, and emerging AI‑driven development patterns. The ideal candidate is a hands-on technologist who can design resilient systems, guide engineering teams, and partner with cross-functional stakeholders to deliver high‑impact customer engagement capabilities Key Responsibilities: Lead end‑to‑end MarTech engineering initiatives across orchestration, data processing, and activation pipelines. Architect scalable, event‑driven systems that power real‑time marketing experiences and automated customer journeys. Design and implement orchestration workflows using Adobe Campaign or equivalent enterprise‑grade tools. Develop high‑performance big‑data applications using Scala, Databricks, Spark SQL, Spark Streaming, and Python. Build and optimize cloud‑native data pipelines on Azure, including ADF‑based ingestion, transformation, and orchestration. Apply modern design patterns to ensure reliability, maintainability, and scalability across distributed systems. Drive AI‑assisted engineering practices including Vibe Coding and other generative‑AI development accelerators. Collaborate with product, marketing, and data teams to translate business needs into robust technical solutions. Mentor engineers and elevate engineering standards, code quality, and operational excellence within the POD. Required Skills: Deep expertise in MarTech platforms with hands‑on experience in Adobe Campaign or similar orchestration tools. Strong proficiency in big‑data technologies: Scala, Databricks, Spark SQL, Spark Streaming, Python. Cloud engineering experience with Azure services, including Azure Data Factory. Advanced system design capabilities including event‑driven architectures and distributed design patterns. Experience with AI‑augmented development such as Vibe Coding or comparable frameworks. Proven ability to lead engineering teams in a fast‑paced, cross‑functional environment. Strong communication and stakeholder alignment skills with the ability to translate technical concepts into business impact.

The Company: A data services company based in the heart of San Francisco, are looking for a Senior Data Engineer. They are a team of passionate engineers and data experts that are working on a variety of different project, primarily in the financial services sector, helping organizations build scalable, modern data platforms. This is a hands-on, full-time role with close collaboration alongside the CTO and senior engineers, offering strong influence over technical direction and delivery. The Role: This is an on-site position in the downtown San Francisco where you will be working as part of a close-knit team, collaborating on projects in their brand new office. You will be working across end-to-end data projects, including: Building and maintaining data pipelines and ETL processes. Sourcing and integrating third-party APIs and datasets. Batch and near-real-time processing (cloud agnostic). Downstream analytics and reporting using tools like Sigma Computing and Omnium Analytics. Collaborating with the CTO and engineering team to deliver client solutions. Key Skills: 5+ years' data engineering experience Strong Python, BigQuery, and cloud (GCP or similar) Solid ETL and pipeline background Comfortable with large-scale data Nice to Have Beam, Dataflow, Spark, or Hadoop Tableau or Looker ML/AI exposure Kafka or Pub/Sub Given the varied nature of the work, a broad range of technology experience is valued. You don't need to have experience with every tool listed below to be considered, so we encourage you to apply. This role is 5 days a week on-site in downtown San Francisco. Looking to pay between $170,000-$220,000 with a bonus between 15-20%. Benefits Health, Dental & Vision covered Unlimited PTO 401(k) with employer contribution Commuter benefits.

The WCIRB is looking for an experienced Lead Actuarial Analyst interested in having a critical role in the WCIRB's actuarial functions. This position will be directly involved in the WCIRB's core ratemaking and data analysis functions with opportunities for growth, independence, and external communication. The Workers' Compensation Insurance Rating Bureau of California (WCIRB) is California's trusted, objective provider of actuarially-based information and research, advisory pure premium rates, and educational services integral to a healthy workers' compensation system. The WCIRB is a California unincorporated, private, nonprofit association comprised of all companies licensed to transact workers' compensation insurance in California, and has over 400 member companies. No state money is used to fund its operations. The operations of the WCIRB are funded primarily by membership fees and assessments. To accurately measure the cost of providing workers' compensation benefits, the WCIRB performs a number of functions, including collection of premium and loss data on every workers' compensation insurance policy, examination of policy documents, inspections of insured businesses, and test audits of insurer payroll audits and claims classification. The WCIRB employs approximately 175 people. The home office is located in San Francisco, California. Summary of Position The Lead Actuarial Analyst is responsible for (1) leading various complex actuarial analyses and core projects, (2) supervising and maintaining data collection processes, and (3) providing input and insight regarding trends, cost drivers, and other key components of the WCIRB's core ratemaking functions. The Lead Actuarial Analyst works independently and collaboratively with other members of the Actuarial Services team, other WCIRB research teams and other WCIRB departments, with little to no supervision, and where work is peer reviewed by other analysts or leaders. The Lead Actuarial Analyst reports to the Vice President, Actuary. Essential Duties and Responsibilities Leads the analysis and evaluation of statistical data pertaining to pure premium rates; identifies trends or cost drivers; prepares materials for committees or rate filings to evaluate impact of various cost drivers on pure premium rates. Leads actuarial analyses of aggregate data and ratemaking methodologies; recommends adjustments to actuarial ratemaking methodologies to the Vice President, Actuary and Chief Actuary; periodically validates appropriateness of methodologies. Provides key deliverables and correspondence with WCIRB members and other customers, such as the insurance department and governmental agencies, on complex data and other technical issues, with minimal or no supervision. Represents Actuarial department and provides subject matter expertise on actuarial data and data collection processes to representatives of other units of the WCIRB on various cross-functional projects and issues. Prepares, reviews, and analyzes various studies of aggregate and classification experience for rate filings and other reports produced by Actuarial Services included those presented to WCIRB Committees and Working Groups. Leads the Actuarial team's efforts in collaboration with the IT department on the development and changes to applications used by the Actuarial team and customers to submit, retrieve, and/or analyze data. Supervises the development and maintenance of data products and oversees the fulfillment of data requirements pursuant to statutory and regulatory mandates. Performs peer reviews of analysts' work. Supervises actuarial analysts in various aspects of analyses; oversees progress of projects and guides projects to completion in an accurate and timely manner. Education, Experience, and Skill Qualifications: Educational background (Bachelor's degree or above) in a technical field such as mathematics, actuarial science, applied statistics, or economics. Five years of experience as an actuarial analyst in a property/casualty insurance company, rating organization, consulting firm, or a state insurance department. Very strong professional communication skills, both verbally and in writing. Strong listening and interpersonal skills. A high level of ability in the utilization of mathematical techniques for the analysis of statistical information. The ability to develop a complete theoretical framework with precisely-defined relationships, as necessary in special studies or rate revisions. Very strong proficiency in the following three areas with six years' experience preferred: mathematics, applied statistics, and programming (in a language such as VBA, SQL, R, or Python). Proficiency in Microsoft Office Suite. Associate of the Casualty Actuarial Society (CAS) or at least six CAS exams with extensive related experience. Perks & Benefits Our employees enjoy a state of the art, energy-efficient, open work environment that nurtures collaboration and creativity. At the WCIRB, we go the extra mile to keep our employees happy and healthy. Proud to be recognized as a Plan Sponsor of the Year finalist for our commitment to retirement readiness through strong 401k and pension offerings. Some of our perks include: Hybrid work environment (40% onsite 60% remote) Medical, dental and vision benefits Competitive PTO Program 401K and pension plan Annual incentive plan Social activities Community volunteer involvement WCIRB is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. The successful candidate will reside in California and will work from our headquarters in San Francisco at least 40% of the time. We are NOT able to pay for relocation costs for candidates or to sponsor or take over sponsorship of an employment Visa at this time. Thank you for your interest in the WCIRB!

About Gap Inc. Our brands bridge the gaps we see in the world. Old Navy democratizes style to ensure everyone has access to quality fashion at every price point. Athleta unleashes the potential of every woman, regardless of body size, age or ethnicity. Banana Republic believes in sustainable luxury for all. And Gap inspires the world to bring individuality to modern, responsibly made essentials. This simple idea-that we all deserve to belong, and on our own terms-is core to who we are as a company and how we make decisions. Our team is made up of thousands of people across the globe who take risks, think big, and do good for our customers, communities, and the planet. Ready to learn fast, create with audacity and lead boldly? Join our team. About the Role Gap Inc. is seeking a Principal Data Scientist with deep expertise in operations research and machine learning to lead the design and deployment of advanced analytics solutions across the Product-to-Market (P2M) space. This role focuses on driving enterprise-scale impact through optimization and data science initiatives spanning pricing, inventory, and assortment optimization. The Principal Data Scientist serves as a senior technical and strategic thought partner, defining solution architectures, influencing product and business decisions, and ensuring that analytical solutions are both technically rigorous and operationally viable. The ideal candidate can lead end-to-end solutioning independently, manage ambiguity and complex stakeholder dynamics, and communicate technical and business risk effectively across teams and leadership levels. What You'll Do * Lead the framing, design, and delivery of advanced optimization and machine learning solutions for high-impact retail supply chain challenges. * Partner with product, engineering, and business leaders to define analytics roadmaps, influence strategic priorities, and align technical investments with business goals. * Provide technical leadership to other data scientists through mentorship, design reviews, and shared best practices in solution design and production deployment. * Evaluate and communicate solution risks proactively, grounding recommendations in realistic assessments of data, system readiness, and operational feasibility. * Evaluate, quantify, and communicate the business impact of deployed solutions using statistical and causal inference methods, ensuring benefit realization is measured rigorously and credibly. * Serve as a trusted advisor by effectively managing stakeholder expectations, influencing decision-making, and translating analytical outcomes into actionable business insights. * Drive cross-functional collaboration by working closely with engineering, product management, and business partners to ensure model deployment and adoption success. * Quantify business benefits from deployed solutions using rigorous statistical and causal inference methods, ensuring that model outcomes translate into measurable value * Design and implement robust, scalable solutions using Python, SQL, and PySpark on enterprise data platforms such as Databricks and GCP. * Contribute to the development of enterprise standards for reproducible research, model governance, and analytics quality. Who You Are * Master's or Ph.D. in Operations Research, Operations Management, Industrial Engineering, Applied Mathematics, or a closely related quantitative discipline. * 10+ years of experience developing, deploying, and scaling optimization and data science solutions in retail, supply chain, or similar complex domains. * Proven track record of delivering production-grade analytical solutions that have influenced business strategy and delivered measurable outcomes. * Strong expertise in operations research methods, including linear, nonlinear, and mixed-integer programming, stochastic modeling, and simulation. * Deep technical proficiency in Python, SQL, and PySpark, with experience in optimization and ML libraries such as Pyomo, Gurobi, OR-Tools, scikit-learn, and MLlib. * Hands-on experience with enterprise platforms such as Databricks and cloud environments * Demonstrated ability to assess, communicate, and mitigate risk across analytical, technical, and business dimensions. * Excellent communication and storytelling skills, with a proven ability to convey complex analytical concepts to technical and non-technical audiences. * Strong collaboration and influence skills, with experience leading cross-functional teams in matrixed organizations. * Experience managing code quality, CI/CD pipelines, and GitHub-based workflows. Preferred Qualifications * Experience shaping and executing multi-year analytics strategies in retail or supply chain domains. * Proven ability to balance long-term innovation with short-term deliverables. * Background in agile product development and stakeholder alignment for enterprise-scale initiatives. Benefits at Gap Inc. * Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees. * One of the most competitive Paid Time Off plans in the industry.* * Employees can take up to five "on the clock" hours each month to volunteer at a charity of their choice.* * Extensive 401(k) plan with company matching for contributions up to four percent of an employee's base pay.* * Employee stock purchase plan.* * Medical, dental, vision and life insurance.* * See more of the benefits we offer. * For eligible employees Gap Inc. is an equal-opportunity employer and is committed to providing a workplace free from harassment and discrimination. We are committed to recruiting, hiring, training and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We have received numerous awards for our long-held commitment to equality and will continue to foster a diverse and inclusive environment of belonging. In 2022, we were recognized by Forbes as one of the World's Best Employers and one of the Best Employers for Diversity. Salary Range: $201,700 - $267,300 USD Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.

At CLARA analytics we build AI-based InsurTech products that help workers' compensation claims examiners get in front of their claims through easy-to-use AI and machine learning. Our CLARA Claims product helps claims managers focus their teams' efforts, while CLARA Providers helps connect the injured worker to the right doctor fast. While there is deep data science behind these solutions, they are packaged in easy-to-use formats that can start delivering value in a few months. Job Description CLARA analytics is looking for extraordinary data scientists to synthesize and leverage ever-growing datasets to help radically transform the operational performance in the workers' compensation sector. The Data Scientist role involves working on all stages of the data science pipeline, from acquiring and assessing data, selecting appropriate models and algorithms and/or deriving custom algorithms, testing and evaluating these algorithms and models, and incorporating them into a commercial product. She/He will work with a team of Data Scientists to create bleeding edge analytic technology. This is a chance to get in early with a rapidly growing Silicon Valley company, and to participate in developing the next generation of truly game-changing, healthcare-related products. Job title and compensation will be adjusted as appropriate to meet the experience level of the right candidate. Qualifications Key Responsibilities Analyze various data sets and build sophisticated mathematical/statistical models Design and optimize algorithms to achieve the best solutions Collaborate with product management and engineering departments to understand company needs and devise possible solutions Keep up-to-date with latest technology trends Communicate results and ideas to key decision makers Implement new statistical or other mathematical methodologies as needed for specific models or analysis Participate in product ideation sessions, roadmap reviews and customer calls as needed. Qualifications & Experience Strong quantitative and analytical skills with an advanced degree in a STEM discipline (Masters required, PhD preferred) Experience using at least two of the following: R, Python, C, C++, SQL, Java. (Experience with Spark/Scala a plus.) Experience defining research hypotheses, analyzing data sets, engineering features and building machine learning mathematical/statistical models and/or optimization algorithms Ability to communicate complex quantitative analysis results in a clear, precise, and actionable manner using a variety of presentation tools including Excel, PowerPoint, etc. Ability to work collaboratively and independently. Personal Characteristics A passion for data science and problem-solving in general Self-driven individual who can take a high level idea and see it through to completion with minimal supervision The desire and ability to work in a fast-paced, start-up atmosphere Takes a pragmatic approach to problem-solving, combined with the ability to thrive under the pressure of constant change and moving objectives Ability to work under tight deadlines and display grace under pressure Willingness to learn about the industry we serve Excellent organizational, interpersonal, and communication skills (both written and verbal). Additional Information At CLARA analytics, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.