Data analyst jobs in Richmond, CA - 2,491 jobs

A data intelligence firm in San Francisco is looking for a Data Analyst to unlock the potential of unique data assets. This role involves collaborating with engineers to solve complex problems, conducting analyses, and generating visualizations. Candidates should have a Bachelor's degree and 2-4 years of relevant experience, with proficiency in SQL. The position offers a competitive salary range of $90,000 - $120,000, along with a comprehensive benefits package. #J-18808-Ljbffr

HockeyStack is an Applied AI company on a mission to automate sales, marketing, and customer success for B2B companies. We build the most complete and accurate picture of the B2B buyer by integrating with every tool your team uses, partnering with third-party data providers, and deploying custom AI research agents. We use this data to power applications that automate high-value, high-complexity workflows across the go-to-market and revenue teams. Our core products include: Marketing Intelligence - instantly answers questions like “What led to that sudden drop in pipeline?” Account Intelligence - surfaces next-best actions to help reps move target accounts toward conversion Since launching in January 2023, we've come through Y Combinator, raised a $26M Series A led by Bessemer. We're growing 3× year-over-year, have hit multimillion ARR, and process over 60 TB of GTM data monthly. Based at our San Francisco HQ, we operate fully in-person, move fast and hire people who are ready to win. 🚀 Your Mission We are seeking a customer-focused Data Analyst to help our clients answer their most important business questions around GTM revenue performance and marketing spend optimization. This is not a heavy data-engineering role; instead, you'll use HockeyStack's platform and available data to guide customers toward impactful insights and recommendations. 🔧 What You'll Do Partner with customers to solve their revenue goals, challenges, and questions. Use HockeyStack's platform to uncover insights and deliver clear, actionable recommendations. Translate complex metrics into straightforward explanations for non-technical audiences. Be the Data Partner to support Customer Success Managers in delivering strategic guidance to clients. Identify patterns and trends in marketing and sales data to advise customers on where to focus efforts. Collaborate with internal teams to continuously enhance the customer experience. 🧩 Core Strengths Business Insight: Ability to connect data to revenue outcomes and business strategy. Customer Orientation: Skilled at understanding client goals and delivering value through insights. Analytical Thinking: Comfortable framing and answering complex questions with data-driven logic. Clear Communication: Able to translate analytics into simple, impactful recommendations. 🧬 What We're Looking For Ownership-first mindset - you take initiative, move fast, and figure things out Thrive in early-stage, high-urgency environments where speed and impact matter Curious, self-aware, and feedback-driven - you bring energy, not ego See this role as a defining chapter - not a stepping stone or side quest Bachelor's degree in Mathematics, Statistics, Data Science, Applied Economics, or a related field. 1-3 years of experience in Data Analytics or Consulting with Analytical focus. Strong preference for candidates with Marketing Analytics or GTM/Sales Analytics Experience. Strong problem-solving skills with the ability to structure and answer key business questions. Excellent communication skills to convey data-driven insights to senior stakeholders. Familiarity with SaaS, B2B marketing, or revenue analytics is a strong plus. Ability to think strategically and recommend actions based on data, without needing to deep-dive into raw datasets. ✨ Why Join Now? We're at an inflection point. The product is proven, the market is massive, and the opportunity is wide open. You'll be joining a company with real traction, rapid growth, and meaningful backing-where every person still shapes the outcome. This isn't just a job. It's a chance to build something category-defining with people who care deeply about doing it right. We're building a high-performing, culture at our San Francisco HQ, where the team collaborates shoulder-to-shoulder. While that's our standard for most roles, this position is uniquely flexible-offering remote options for exceptional candidates based in the U.S. or internationally, as long as you're fully available during U.S. business hours. The base salary range for this role is $40,000 to $120,000 USD, adjusted for location, experience, and qualifications. HockeyStack is proud to be an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other legally protected status. We celebrate diversity and are committed to fostering an inclusive environment for all employees. #J-18808-Ljbffr

A healthcare solutions company seeks an Analyst in San Francisco. You'll analyze healthcare data, build dashboards, and provide actionable insights to leadership. Ideal candidates have 2+ years in analytical roles and should be proficient in SQL and Excel. This position offers the chance to make a significant impact as the first analyst in a fast-paced environment, with opportunities for growth and innovation in consumer healthcare. #J-18808-Ljbffr

A financial technology company is looking for a Data Analyst in San Francisco to transform data into actionable insights. The role involves writing SQL queries, building visualizations, and identifying trends to inform product decisions. With experience in SQL and data visualization tools like Tableau, candidates should possess strong analytical and communication skills. An ability to analyze financial data accurately is essential, as the role directly influences company strategy and product roadmaps. Competitive salary range is offered. #J-18808-Ljbffr

A leading AI analytics company in San Francisco is hiring a Data Analyst to build and scale its analytics capabilities. The role involves creating dashboards, defining metrics, and collaborating with various teams. Ideal candidates should have strong SQL skills and 3+ years of experience in analytics. This company offers competitive compensation and comprehensive benefits, including health insurance and generous PTO. #J-18808-Ljbffr

Type: Full-Time Compensation: Competitive salary + early-stage equity Backed by 8VC, we're building a world‑class team to tackle one of the industry's most critical infrastructure problems. About the Role We're building an AI‑native platform where industrial data becomes actionable through semantic enrichment, intelligent agents, and governed interoperability. At the heart of this architecture lies our Data Fabric - an intelligent, governed layer that unifies fragmented and siloed data streams into knowledge graphs ready for high context decision‑making and agentic execution. The Data Partnerships Analyst will be on the front lines of this strategy: researching, evaluating, and supporting partnerships with leading data providers (trade, compliance, entity mapping, financial, ESG, geopolitical, etc). You'll play a critical role in mapping data ecosystems, structuring partnerships, and ensuring Fabrion's platform is powered by the most complete, high‑quality, and strategically differentiated data. This role is ideal for someone with sharp analytical skills, a curiosity for data‑driven businesses, and a strong interest in how AI and partnerships intersect to transform global value chains. Responsibilities Market Landscaping & Research: Identify, track, and evaluate relevant data providers across global markets. Deal Support: Assist in structuring partnership discussions, including preparing briefs, evaluating contract terms, and surfacing risks or dependencies. Data Evaluation: Assess sample datasets for coverage, quality, refresh frequency, schema design, and interoperability with Fabrion's knowledge graphs. Partnership Pipeline: Maintain CRM‑style tracking of outreach, engagements, and deal status across priority providers. Competitive Intelligence: Benchmark competitors' data strategies and build landscape views of potential threats and opportunities. Cross‑Team Collaboration: Work with product, engineering and legal teams to translate data partnership requirements into technical and contractual frameworks. What We're Looking For Core Experience 3+ years experience in research, consulting, corporate strategy, business development or partnerships. Experience in the automotive industry, particularly at an OEM and/or Tier 1 supplier, is a huge plus. Strong analytical skills; comfort with messy datasets, Excel/Sheets, and SQL/Python basics. Excellent communication and synthesis skills - able to distill complex market landscapes into crisp takeaways. Exposure to B2B SaaS, data vendors, or enterprise technology ecosystems preferred. Mindset Systems thinker: curious about how fragmented datasets connect into real‑world decision and execution systems. Comfortable navigating ambiguity and building processes from scratch. High ownership: proactive, organized, and reliable in pushing workstreams forward. Excited to work closely with founders and investors in a fast‑paced, high‑stakes environment. Bonus Skills Prior experience evaluating or working with data providers (e.g., S&P, D&B, etc). Understanding of trade data, entity mapping, risk and compliance frameworks (REACH, RoHS, ESG, sanctions). Familiarity with data licensing, APIs, or data feeds. Prior exposure to supply chain, automotive, or industrial domains. Why This Role Matters Our platform's intelligence is only as strong as the data it is built on. The Data Partnerships Analyst helps ensure Fabrion gains early access to the most critical and differentiated data sources. This role gives you direct exposure to startup founders, investors, and senior executives at leading data providers. You'll develop a unique perspective at the intersection of data, AI, and industrial transformation, while shaping the partnerships that power Fabrion's AI agents. If you're excited to map the global data landscape, help secure strategic partnerships, and build the foundation of an AI‑native enterprise platform, we'd love to hear from you! #J-18808-Ljbffr

We are seeking a Data Analyst to join our team in San Francisco. The successful candidate will be responsible for analyzing data to help drive business decisions and improve operational efficiency. Collect, process, and analyze data from various sources. Generate reports and visualizations to present findings. Collaborate with stakeholders to understand their data needs. Identify trends and patterns in data to inform strategy. Qualifications A strong analytical mindset, proficiency in data analysis tools, and excellent problem-solving skills are required for this position. How to apply Please fill out your details and answer the various questions in this application form. A company is nothing without its people. We attract great people who always want to learn and improve both themselves and their team. By getting 1% better every day we provide the best possible service & results for our clients. We are a team of world-class ads experts, enabling Amazon brands and aggregators to achieve the best possible results. #J-18808-Ljbffr

The Role As a Data Analyst at Zencastr, you will partner with different departments and teams to make data-driven decisions that ship better products by delivering product insights and strategic recommendations based upon quantitative analysis. You will be involved in driving data-based decisions and lead initiatives to improve operational efficiency. You will be an active thought partner and subject matter expert in your data, deeply involved in new projects and all aspects of your stakeholders deliverables. We are searching for the right candidate who has strong experience analyzing and reporting on acquisition, conversion and user retention metrics to measure the impact of campaigns. What You'll Do.. Partner across departments to build a rapport and be a trusted advisor to team members; Use an analytical perspective to inform decision making and help drive a focus on the most impactful ideas Navigate ambiguity of stakeholder requests and formulate hypotheses while building consensus Design and build advanced analytical solutions and products to deliver superior business outcomes using research and performing quantitative and qualitative analysis Identify trends and opportunities to drive product growth and nurture a healthy ecosystem Use BI tooling, construct core dashboards, visualizations, and analyses to help stakeholders monitor product health and make better decisions Communicate insights to stakeholders distilling complex analysis into accessible learnings; Deliver effective presentations to influence multiple levels of stakeholders Continuously improve your business acumen and understanding of Zencastr products and business, as well as the podcast/creator industry at large Understand underlying data sources and their limitations and communicate complex data insights through exploratory analysis and research to suggest improvement Conduct research on various business processes to uncover bottlenecks and provide recommendations to improve and align with the business goal Analyze various business-related effects, e.g. product optimization and improvement, market activity analysis, operation analysis, etc Collaborate with the operation team, analyze business operation efficiency, identify business problems, and provide optimization suggestions to improve operating efficiency If This Describes You.. 3+ years of data analytics experience, preferably for SaaS companies Strong SQL - experience navigating and working with data sets and developing data pipelines using SQL Has strong experience analyzing and reporting on acquisition, conversion and user retention metrics to measure the impact of campaigns Undergraduate degree in quantitative major (Finance, Economics, Math, Computer Science) or equivalent experience Experience working with Product, Engineering, Sales & Operation teams Foundational understanding of data modeling best practices Experience using BI visualization tools like Metabase, Looker, Power BI or Tableau Experience using Analytics tools like Google Analytics, FullStory, Heap, Amplitude, Mixpanel Able to summarize, explain and simplify complex data analyses and concepts Ability to manage multiple deliverables simultaneously and proactively communicate changes and roadblocks Comfortable working collaboratively with various stakeholders across departments, including senior management Motivated to find a faster way to do your least favorite tasks #J-18808-Ljbffr

At Neuroverse HealthTech, we are revolutionizing workplace wellness with cutting edge solutions that prioritize mental health, inclusivity, and resilience. Founded with a vision to create workplaces where every individual thrives, we empower organizations with tools to detect burnout, foster engagement, and support neurodiverse teams. Our mission is simple yet powerful: to transform workplaces into spaces of care, innovation, and growth by integrating mental health at the core of organizational success. At Neuroverse, our culture is our strength. We are a playground for creativity and collaboration, were diverse perspectives fuel innovation. As a team, we value empathy, inclusivity, and a relentless commitment to learning and growth. Joining Neuroverse means being part of a dynamic environment that encourages big ideas, fosters professional development, and rewards impact. When you grow, we grow. At Neuroverse, we're not just building a business. We are building a movement to redefine workplace wellness globally. Come, be a part of our journey and make a difference where it truly matters. The work: Plans and leads the consultation process for complex research projects to support development and alumni engagement across UBC. Leads and delivers major quantitative research initiatives that identify prospective donors, determine trends, forecast growth opportunities and provide strategic understanding of patterns in alumni and donor behavior. Provides statistical data analysis to support fundraising targets and policy objectives, using regression analysis, time series analysis, predictive modelling and segmentation, machine learning algorithms, text analysis, and spatial analysis. Participates in the development of policies and performance metrics and tracks and reports on results. Demonstrates the impact of performance and focuses on efficient and effective services. Develops and designs methodologies and standards to produce regular statistical reports. Documents all necessary business and technical details related to data analytics outputs, and uses in-house version control and project management tools to track and report on progress. Implements all stages of analytics projects. Contributes to the development of business cases, project plans, status reports, scope, deliverables and timelines related to small to medium data analytics projects Prepares information using data visualization techniques for analytics reports, proposals and presentations for UBC executive, Alumni Association Board, UBC Board of Governors and DAE leadership. Develops self-serve tools such as interactive reports and dashboards to meet the data analytics needs for DAE. Imparts understanding of complex technical ideas and results to non-technical audiences through the effective use of words, infographics and interactive data visualizations. Extracts, cleans, transforms, and synthesizes structured and unstructured internal UBC data and external data. Remain current on DAE s data sources, and ensure integrity, quality, security, and a high degree of usability for data used in analysis and resulting metrics, scores and attributes. Collaborates on the integration of data analytics outputs into CRM, design and delivery of training materials and sessions to DAE staff. Researches and develops current and emerging trends in philanthropy, alumni engagement, higher education and complex data analysis. Liaises and collaborates with other UBC departments and other universities. Qualifications: Bachelor's degree or higher in relevant field in Computer Science or Medical Health Information, or equivalent qualifications/experience At least three years of experience in data analysis, as well as data exploration and presentation Experience with SAS and SQL programming languages Experience working with a variety of information systems and data files, including large and complex files: analysing file structure; using and creating file layouts; and transforming raw data into finished products Experience using advanced Excel features and techniques Familiarity with healthcare data is an asset Ability to self-motivate and work independently, as well as work collaboratively as part of a team Project leadership and management skills Excellent oral and written communication Ability to work under pressure to meet deadlines Knowledge of HIV/AIDS, viral hepatitis, and/or health sciences research is an asset, but not necessary An understanding of epidemiologic research (e.g., study design, bias) is an asset. Job Category: Technology Job Type: Full Time Job Location: Brisbane City Australia Dharamshala HP India London UK San Francisco CA United States #J-18808-Ljbffr

A cutting-edge technology company located in San Francisco is seeking a Data Analyst to power its new revenue operating system. The successful candidate will be responsible for building metrics and dashboards, providing strategic insights to leadership, and ensuring high-quality data foundations. This role is ideal for someone with strong SQL and Python skills, experience in fast-paced environments, and the ability to communicate complex data in simple terms. Competitive pay and benefits are offered. #J-18808-Ljbffr

HQ Numeral is building the automation backbone for internet commerce - starting with the painful world of sales tax compliance. We handle everything from registration to remittance, delivering a white-glove service so e-commerce businesses can stay laser-focused on what they do best: growing their products, customers, and teams. We're one of the fastest-growing companies from Y Combinator's W23 batch, backed by top-tier investors including Benchmark Capital. Our team has deep roots from the early days at Stripe, Airbnb, Notion, and other breakout companies - and now we're bringing that same level of craft, speed, and ambition to a space that's long overdue for reinvention. Numeral is small but mighty. Growth is already border-line unmanageable - which means every hire we make now will directly shape the trajectory of the company. If you're excited about joining as an early team member and want the kind of ownership that defines careers, we want to meet you. Mission Running an online business today means wearing a thousand hats - most of them not the reason founders started their company. Our mission is to eliminate the administrative and accounting burdens that distract businesses from doing what they love. We've already helped hundreds of merchants avoid the headache of building giant finance teams just to manage tax compliance. Tomorrow, we're scaling that impact even further: building the automation layer that lets internet businesses stay nimble, compliant, and future-proof. About the role: As a Data Analyst at Numeral, you'll be embedded in the engine room of our operations-playing a critical role in reconciling customer data, improving data quality, and making our platform smarter and more scalable. You'll work closely with Engineering, Product, and CX teams to ensure customers have clean, actionable data at their fingertips and smooth onboarding experiences. This is a foundational role with outsized impact. You'll get to shape how we use data across the business - no bureaucratic layers, just real ownership and real outcomes. Responsibilities: Reconcile financial and transactional data from multiple sources to enable accurate, repeatable sales tax filings Normalize customer data across platforms (e.g. Stripe, Shopify, Numeral API) to ensure integrity in tax workflows Partner with Sales, Engineering, Product, and Solutions teams to troubleshoot and resolve onboarding data issues Support our customer-facing teams with ad hoc data questions, investigations, and insights Build internal tooling and processes to streamline reconciliation and improve onboarding throughput Improve the fidelity and performance of our DBT pipelines and help evolve our broader data architecture Qualifications: Proficient in SQL and Excel / Google Sheets Strong analytical and pattern recognition skills across large, messy, or multi-source datasets Experience reconciling financial or transactional data (ideally in an e-commerce or payments environment) Strong problem-solving skills and ability to operate with autonomy in fast-moving environments Clear communicator with high attention to detail and a collaborative mindset Bonus Points For: Experience with DBT or similar ETL frameworks Familiarity with Stripe, Shopify, Fivetran, Parquet, S3, DuckDB Comfort navigating REST APIs and programmatically transforming data (e.g. Python or other scripting languages) Prior exposure to tax, compliance, or accounting-related data A background in operations, finance, or technical customer success Why Join Us? Be a core builder in an ambitious, globally minded startup. Learn hands-on how to scale international compliance systems. Work across functions and with leadership early in your career. Make a visible impact immediately through enablement and operational design. Enjoy a flexible, remote-first culture with strong mentorship and ownership opportunities. #J-18808-Ljbffr

JOB TITLE: Staff Data Scientist DURATION: Full-time Key Responsibilities: Lead the design, development, testing, and global deployment of large-scale time series forecasting models (including Regression models and state of the art time series specific models for example N-BEAST, PatchTST) to support complex retail and e-commerce hierarchies. Introduce causal modeling approaches to conduct impact analysis for future forecast. Continuously enhance forecasting strategies by incorporating advanced machine learning architectures, including RNNs (sequence modeling), CNNs (temporal feature extraction), and Attention-based mechanisms to improve accuracy, scalability, and robustness in time series forecasting. Advance causal modeling frameworks to quantify event impacts and integrate causal insights into forward-looking forecasts. Build and maintain experimentation pipelines (A/B testing, quasi-experiments, multi-armed bandits) for evaluating causal impacts of interventions. Mentor junior scientists, review research and production code, and ensure reproducibility and scalability in pipelines. Collaborate with engineering to implement forecasting + optimization systems in production (Airflow, Astronomer, Spark/Ray). Act as technical lead on multiple projects, balancing research rigor with business delivery. Must Have Requirements: Strong foundation in Causal Inference, Statistical Analysis, and advanced Machine Learning methods Hands-on experience with a wide range of ML techniques, with a deep understanding of their advantages and limitations across different scenarios. Ability to integrate statistical expertise with machine learning methods to maximize the value and interpretability of ML solutions. Proficiency in Python, SQL, PyTorch, Spark/Ray, and stats/econometrics libraries. Experience deploying ML systems at scale on cloud platforms (GCP/Azure). Plusses: Publications and open-source contributions spanning the full spectrum of modern Machine Learning, from Statistical Learning (e.g., Bayesian modeling, causal inference, high-dimensional statistical methods) to Deep Learning (e.g., convolutional and transformer-based architectures) and Reinforcement Learning (e.g., dynamic programming, policy gradient methods). Exposure to ML observability: drift detection, retraining triggers, and causality-informed monitoring. Timeseries - will be working on it but can learn on the job Job Description: Chance to work on financial data for complex problems/challenges. Utilize LLMs/Genai systems and architectures to build and deploy state-of-the-art Genai systems. Our team collaborates closely with Finance teams to enhance financial planning and strategic decision-making through cutting-edge data-driven solutions. We specialize in a range of initiatives which provides actionable insights into trends and patterns and leveraging Generative AI (Genai) to produce concise, insightful summaries that empower decision-makers. By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations. About Team: Our team works closely with our US stores and eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, we offer an extensive selection that our customers value, whether they shop online , through one of our mobile apps, or in-store. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization.

Job Title: Data Scientist - All Levels (Manager, Principal, Staff) Bentonville, AR (relocation package available only for Bentonville) Duration: Full Time IV Process: Pre-screening Three virtual client rounds (plus an additional round for Manager level) Multiple interviews can be scheduled in one day Positions Available (Exclusive): 1 Manager of Data Science 1 Principal Engineer of Data Science 3 Staff Engineers of Data Science Core Must-Have Skills Across All Levels Generative AI (Gen AI) Large Language Models (LLM, GPT, BERT, RAG) Time Series Modeling / Forecasting Prompting & Fine-Tuning Managerial/leadership experience per level (Manager → mid-size team, Principal → top of team, Staff → lead-level experience) Role-Specific Job Description Manager of Data Science Responsibilities: Lead a team of data scientists and ML engineers Build and deploy Gen AI and traditional ML applications for Walmart Finance Drive cross-functional projects in NLP, LLM, timeseries forecasting, and recommendation systems Maintain technical and business knowledge, mentor team members Requirements: Experience managing mid-size internal team of DS/MLEs Experience in NLP, LLMs, timeseries, traditional ML for retail/e-commerce Strong organizational, interpersonal, and cross-functional collaboration skills Principal Data Scientist Responsibilities: Develop LLM-powered intelligent systems (Q&A, recommendations, autonomous agents) Collaborate cross-functionally with DS, MLEs, UX, and product teams Deploy scalable AI/ML solutions, mentor junior DS Contribute to internal/external AI/ML research Requirements: Proven deployment of high-risk NLP applications in production Strong ML foundations (statistics, optimization, DL) Advanced proficiency in Python, ML/DS libraries, deep learning frameworks Familiarity with ML infra (Kubeflow, MLflow, Airflow) Bonus Skills: Text-to-SQL/Text-to-Cypher, recommender systems, fine-tuning LLMs, publications in top-tier ML/NLP venues Staff Engineer of Data Science Responsibilities: Lead data-driven projects for Finance using LLMs/Gen AI Build, deploy, and productionize AI/ML solutions for large-scale applications Collaborate cross-functionally with stakeholders and business owners Requirements: Master's/PhD in Statistics, Analytics, CS, or related field with 5+ years experience Hands-on experience with LLMs, Gen AI ecosystems (GPT, LLaMA, Mistral, Claude, Gemini, AWS Sonnet) RAG, AI agent development, LangChain, LangGraph Strong solution architecture mindset and problem-solving skills Nice-to-Have: Big Data/Spark experience, Cloud ML (GCP, Azure), GPU DL training Behavioral Qualifications: Adaptable, problem-solver, technically strong, collaborative, able to manage multiple priorities

Chance to work on financial data for complex problems/challenges. Utilize LLMs/Genai systems and architectures to build and deploy state-of-the-art Genai systems. Our team collaborates closely with Finance teams to enhance financial planning and strategic decision-making through cutting-edge data-driven solutions. We specialize in a range of initiatives which provides actionable insights into trends and patterns and leveraging Generative AI (Genai) to produce concise, insightful summaries that empower decision-makers. By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations. About Team: Our team works closely with our US stores and eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, extensive selection that our customers value, whether they shop online through one of our mobile apps, or in-store. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization. What you'll do Lead the design, development, testing, and global deployment of large-scale time series forecasting models (including Regression models and state of the art time series specific models for example N-BEAST, PatchTST) to support complex retail and e-commerce hierarchies. Introduce causal modeling approaches to conduct impact analysis for future forecast. Continuously enhance forecasting strategies by incorporating advanced machine learning architectures, including RNNs (sequence modeling), CNNs (temporal feature extraction), and Attention-based mechanisms to improve accuracy, scalability, and robustness in time series forecasting. Advance causal modeling frameworks to quantify event impacts and integrate causal insights into forward-looking forecasts. Build and maintain experimentation pipelines (A/B testing, quasi-experiments, multi-armed bandits) for evaluating causal impacts of interventions. Mentor junior scientists, review research and production code, and ensure reproducibility and scalability in pipelines. Collaborate with engineering to implement forecasting + optimization systems in production (Airflow, Astronomer, Spark/Ray). Act as technical lead on multiple projects, balancing research rigor with business delivery. What you'll bring Strong foundation in Time Series Forecasting, Causal Inference, Statistical Analysis, and advanced Machine Learning methods Hands-on experience with a wide range of ML techniques, with a deep understanding of their advantages and limitations across different scenarios. Ability to integrate statistical expertise with machine learning methods to maximize the value and interpretability of ML solutions. Proficiency in Python, SQL, PyTorch, Spark/Ray, and stats/econometrics libraries. Experience deploying ML systems at scale on cloud platforms (GCP/Azure). Great to have Publications and open-source contributions spanning the full spectrum of modern Machine Learning, from Statistical Learning (e.g., Bayesian modeling, causal inference, high-dimensional statistical methods) to Deep Learning (e.g., convolutional and transformer-based architectures) and Reinforcement Learning (e.g., dynamic programming, policy gradient methods). Exposure to ML observability: drift detection, retraining triggers, and causality-informed monitoring. Background in retail, e-commerce, or operations analytics. About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit ************************ US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Recruiter Details: Recruiter name: Ajeet Kumar Recruiter's email id : ***************************** JobDiva ID :: JobDiva # 25-53396

A data management company is looking for recent graduates with a chemistry or material science background to help structure customer datasets. The role involves preparing data for a web platform used by scientists and engineers. Applicants should be interested in software engineering, have proficiency in Microsoft Excel, and coding experience in Visual Basic or Python is preferred. This position offers competitive salary, health insurance, and 401K benefits. Position located in San Francisco, California. #J-18808-Ljbffr

A data intelligence company in San Francisco is seeking a Data Analyst to aggregate and analyze data, create visualizations, and collaborate with cross-functional teams. The ideal candidate will have a Bachelor's degree and 2-4 years of experience including internships. Proficiency in SQL and strong communication skills are essential. This role offers a salary range of $90,000 to $120,000 annually and supports a collaborative culture focused on making a difference. #J-18808-Ljbffr

ABOUT BASETEN Baseten powers inference for the world's most dynamic AI companies, like OpenEvidence, Clay, Mirage, Gamma, Sourcegraph, Writer, Abridge, Bland, and Zed. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. With our recent $150M Series D funding, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction, we're scaling our team to meet accelerating customer demand. THE ROLE We're hiring a Data Analyst to help build and scale our internal analytics capabilities. This is a foundational role where you'll create dashboards and data models to power business and product teams alike. You'll collect requirements, define key metrics, and deliver insights directly to stakeholders. You'll also lead your own projects to enable low-friction, self-service access to data across Baseten. RESPONSIBILITIES Build, enhance, and maintain dashboards across multiple functions with a focus on accuracy, simplicity and user experience Ingest and transform raw data into dashboard-ready views using tools like dbt, Airbyte, and BigQuery Partner with Engineering, Finance, Marketing, and Sales teams to understand goals and translate them into data solutions Define and instrument core metrics around ROI, product adoption, customer lifecycle and financial performance Ensure data reliability and consistency through testing, version control and documentation across the analytics stack REQUIREMENTS 3+ years of experience in analytics, BI, or data engineering roles Strong SQL skills with the ability to write complex queries for data transformation and analysis Familiarity with modern BI platforms like Sigma or Hex Prior experience supporting B2B GTM organizations across the customer journey, with hands on experience in a CRM/CDP system Excellent communication skills and a collaborative approach to working with cross-functional teams An ownership mindset: you're excited to be the first hire in this role and to shape how data works at Baseten BENEFITS Competitive compensation, including meaningful equity. 100% coverage of medical, dental, and vision insurance for employee and dependents Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) Paid parental leave Company-facilitated 401(k) Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. #J-18808-Ljbffr

What you'll do... Join Client as a Principal Data Scientist to lead the development and deployment of advanced analytical models that drive strategic business decisions. This role requires expertise in machine learning, statistical analysis, and coding to design scalable solutions addressing complex business challenges. The position involves collaborating across functions to translate data insights into actionable strategies, mentoring team members, and ensuring high-quality data sourcing and validation. The ideal candidate will apply innovative techniques to enhance data-driven decision-making and contribute to Client's continued growth and operational excellence. About the team: The Data Science team employs advanced analytical and modeling techniques to address complex business challenges. They specialize in model assessment, validation, and deployment using tools such as Python, SQL, and machine learning frameworks. Collaborating closely with business stakeholders, the team translates requirements into actionable insights and data-driven solutions. Emphasizing rigorous statistical methods and data visualization, they ensure clear communication of findings. The team promotes continuous learning and innovation, guiding members in best practices and emerging technologies to deliver impactful results aligned with business goals. What you'll do: Develop and implement advanced machine learning models to address complex business challenges and drive data-informed decisions. Lead exploratory data analysis, feature engineering, and statistical modeling to extract actionable insights from data sources. Collaborate with cross-functional teams to translate business requirements into scalable data science solutions aligned with strategic objectives. Oversee model validation, tuning, deployment, and lifecycle management to ensure accuracy, robustness, and sustainability. Mentor and guide team members on analytical techniques, coding best practices, and data visualization to enhance overall team capability. Communicate findings effectively to stakeholders, supporting data-driven decision-making and continuous improvement initiatives. What you'll bring: Extensive experience in developing and deploying machine learning models using Python and related frameworks. Proficiency in advanced statistical analysis and data visualization techniques to derive actionable business insights. Strong knowledge of data sourcing, quality assessment, and management within complex business environments. Expertise in model validation, tuning, and lifecycle management to ensure robust and scalable solutions. Ability to translate business requirements into technical strategies and lead cross-functional teams effectively. Familiarity with cloud platforms such as AWS SageMaker for scalable model development and deployment. Demonstrated leadership in mentoring associates and driving continuous improvement in data science practices. Minimum Qualifications... Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications. Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field Preferred Qualifications... Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications. Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Client's accessibility standards and guidelines for supporting an inclusive culture. About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit ************************ US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Ensures effective and efficient operations through conducting operations analyses (i.e. operational effectiveness and capacity utilization), and recommends improvements. Details Job ID-26-00519

A fast-growing AI company in San Francisco is seeking a customer-focused Data Analyst to help clients answer important questions around revenue performance and marketing strategies. You will translate complex data into insights, support customers in optimizing their efforts, and work collaboratively to enhance the customer experience. The role offers flexibility for exceptional candidates, with a salary range of $40,000 to $120,000 based on experience and location. #J-18808-Ljbffr