Data Scientist Jobs in San Francisco, USA

Senior Data Scientist, AI & App Experience at Chime. Apply directly on Chime's jobs board.

<div class="content-intro"><h2>About us</h2> <div>PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.</div> <div>We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.</div></div><h3><strong>Who We're Looking For</strong></h3> <div>As a Data Scientist in Delivery, you are a problem solver and builder who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, and you excel at working directly with customers (and often side-by-side with them on-site) to transform cutting edge AI models into tools that are useful and used.</div> <div> </div> <div>You’ve worked on difficult problems that require strong foundations in data driven modelling and deep learning techniques, with hands-on experience in probabilistic methods and predictive modelling. Expertise in python, along with proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with the ability to deploy scalable, production-ready models and data pipelines.</div> <div> </div> <div>With at least 1 year industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re truly excited about growing your technical expertise and are naturally inclined to take ownership of data science work streams, continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.</div> <div> </div> <h3><strong>This Role</strong></h3> <div>In this role, you’ll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving.</div> <div>You’ll build the foundations for successful, impactful solutions by:</div> <div> </div> <div> <ul> <li>Pre-processing and analyzing data to prepare it for use in predictive modelling, building the foundation for machine learning algorithms to be developed.</li> <li>Developing and utilizing innovative deep learning models in combination with state-

<p><strong>Location: </strong>San Francisco, CA (Hybrid) </p> <p><strong>What is Verse? </strong></p> <p>Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.</p> <p>Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, <strong>Aria</strong>, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.</p> <p><strong>The Role</strong></p> <p>Verse is seeking an experienced<strong> </strong>Senior Data Scientist, Infrastructure to join our Data Science Team. In this position, you will play a key role in advancing cutting-edge forecasting algorithms to support the operation of distributed battery storage, demand response, and renewable energy. This is a senior role where you will lead the design, development, and deployment of advanced machine learning models powering Verse software offerings related to distributed battery storage. You will work closely with other data science team members and software engineers to deliver production-grade machine learning solutions.Your research will help our customers deploy and operate renewable energy and battery storage resources, and will contribute to the transition toward a low-carbon economy. As a member of the Verse team, you will work in an interdisciplinary and collaborative environment where your expertise in machine learning, data science, and energy systems will be key to delivering impactful solutions.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li><strong>Machine Learning/Data Science:</strong> Apply machine learning, data science and statistical methods to advance Verse forecasting capability that is embedded in our software offerings.</li> <li><strong>Forecasting Methods:</strong> Be responsible for forecasting workflows that inform optimization methods to control battery storage systems, demand response, and other types of electricity market participation.</li> <li><strong>Statistical Analysis: </strong>Use statistical methods to support decision making under uncertainty.</li> <li><strong>Data Analysis and Modeling:</strong> Use advanced data analysis techniques, s

<p><strong>Location: </strong>San Francisco, CA (Hybrid) </p> <p><strong>What is Verse? </strong></p> <p>Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.</p> <p>Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.</p> <p><strong>The Role</strong></p> <p>Verse is seeking a Senior Data Scientist, Forecasting to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and Behind-The-Meter (BTM) battery storage. You will play a critical role in shaping our modeling and analytical data layer, leveraging machine learning techniques, supporting optimization modeling infrastructure, and developing scalable approaches to power Verse’s software offerings.</p> <p>This position emphasizes strong technical depth in Python, machine learning, and analytical modeling, along with the ability to independently scope and execute complex projects end-to-end. Experience in electricity markets and energy systems is preferred.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li><strong>Lead End-to-End Data Science Projects: </strong>Own and drive large projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions with minimal oversight.</li> <li><strong>Statistical & Machine Learning Modeling: </strong>Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models, optimization-linked models) to support decision-making and enhance product capabilities.</li> <li><strong>Analytics Engineering & Data Modeling: </strong>Perform complex data transformations and develop well-structured analytical data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets, with an emphasis on dimensional modeling and reproducibility (e.g., dbt-style workflows)

<p><strong>Location: </strong>San Francisco, CA (Hybrid) </p> <p><strong>What is Verse? </strong></p> <p>Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.</p> <p>Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.</p> <p><strong>The Role</strong></p> <p>Verse is seeking a Data Scientist to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and energy risk management. You will shape the machine learning and data modeling foundations that Verse's software is built on. For example, you might spend a cycle deploying electricity market price forecasting pipelines for new regions, developing solar production anomaly detection models, or creating scalable tools for benchmarking energy project financial performance.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li><strong>Lead End-to-End Data Science Projects: </strong>Own and drive projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions.</li> <li><strong>Statistical & Machine Learning Modeling: </strong>Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models) to support decision-making and enhance product capabilities.</li> <li><strong>Analytics Engineering & Data Modeling: </strong>Perform complex data transformations and develop well-structured data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets.</li> <li><strong>Software Development & Productionization: </strong>Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems in a cloud-based environment while leveraging AI coding tools to accelerate development.</li> <li><strong>MLOps: </strong>

Senior Data Scientist, Product & Growth at Comfy org. Apply via Ashby.

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We’re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.   Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall’s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.   Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We’ve built a product customers love and a business that’s scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines. At Aircall, you’ll join a company in motion. We’re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.   How we work at Aircall: We’re customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you’ll feel at home here. About the team Our Data team is the backbone of Aircall’s decision-making process, driving product development and business growth with cutting-edge data products, tools, and actionable insights   About the role As a Data Scientist, you will provide invaluable insights to our product and business teams, working closely with our product and engineering leaders. You'll support impactful initiatives including pricing, packaging, multi-product strategies and self-service approaches. You will collaborate cross-functionally with Engineering, Sales, Finance, Marketing, and Customer Relations to translate data needs into powerful solutions. You'll also establish best practices in analytics and mentor team members, ensuring high standards in data governance and insight generation.

Senior Data Scientist, Lending at Chime. Apply directly on Chime's jobs board.

Data Scientist, Underwriting at Parafin. Apply via Ashby.

Data Scientist at Parafin. Apply via Ashby.

People Research Data Scientist, AI Fairness & Bias at Openai. Apply via Ashby.

Data Scientist, Platform and B2B Products at Openai. Apply via Ashby.