Data Scientist Jobs in San Francisco, USA

<div class="content-intro"><p>At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.</p> <p>We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.</p> <p>To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.</p> <p>Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.</p> <p>If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.</p></div><p><strong>WHAT YOU'LL DO</strong></p> <p>As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:</p> <ul> <li>Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration</li> <li>Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components</li> <li>Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms</li> <li>Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise</li> <li>Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success</li> </ul> <p><strong>WHO YOU ARE</strong></p> <ul> <li>Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred</li> <li>Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred</li> <li>Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost,

<h2><strong>Who we are</strong></h2> <h3><strong>About Stripe</strong></h3> <p>Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.</p> <h3><strong>About the team</strong></h3> <p>Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We’re looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact.  Our work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.</p> <h2><strong>What you’ll do</strong></h2> <h3><strong>About the internship experience</strong></h3> <p>Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products. </p> <p>Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission. As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results.</p> <p>We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry.</p> <h3><strong>Responsibilities</strong></h3> <p>You will:</p> <ul> <li>Partner closely with Da

Data Scientist at Middesk. Apply via Ashby.

Lead Data Scientist at Middesk. Apply via Ashby.

Data Scientist at Triumph arcade. Apply via Ashby.

Actuarial Data Scientist at Shepherd. Apply via Ashby.

<h2><span style="font-family: helvetica, arial, sans-serif;"><strong>About the role</strong></span></h2> <p class="p2">We're looking for a Sr. Growth Product Data Scientist to partner with our Growth Product and Engineering teams to drive measurable impact across the member journey — from acquisition to conversion through long-term retention. You'll turn data into the decisions that shape how millions of members discover, direct deposit, and get value from Chime.</p> <p class="p2">This role sits at the intersection of product, data, and experimentation. You'll own funnels end-to-end, design and analyze A/B tests, and translate ambiguous business questions into clear, prioritized recommendations that ship.</p> <p class="p3">In this role, you will work closely with product managers, design, engineers, product & lifecycle marketing, and operational stakeholders to foster a data-driven product development culture, advise our product roadmaps, and build a deep understanding of member behavior.</p> <p class="p3">The base salary offered for this role and level of experience will begin at $133,000 and go up to $185,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.</p> <h2><span style="font-family: helvetica, arial, sans-serif;"><strong>In this role, you can expect to</strong></span></h2> <ul class="ul1"> <li class="li3">Operate as an independent thought partner to Product, Engineering, and Design — helping shape strategy, not just measure it. You’ll proactively identify opportunities and risks, framing the right questions before they’re even asked.</li> <li class="li3">Work with the team to develop a rich program of experimentation and A/B testing to improve member product experiences, including metric creation, experiment design, power analysis, and analysis of experiment results.</li> <li class="li3">Drive data-informed decision making within Growth org by equipping PMs and engineers with self-service analytics tools, and conducting ad hoc analyses and causal studies for the team.<span class="Apple-converted-space"> </span></li> <li class="li3">Use advanced statistical methods for causal inference, as well as time-series and other forecasting techniques, to solve product questions for the team. Occasionally apply machine learning methods for problems such as customer segmentation.<span class="Apple-converted-space"> </span></li> <li class="li3">Build metrics to measure user funnels, product engagement, and retention, a

<h2><span style="font-family: helvetica, arial, sans-serif;"><strong>About the role</strong></span></h2> <p><span style="font-family: helvetica, arial, sans-serif;">As a Sr. Trust & Safety Product Data Scientist, you will have the opportunity to develop, test, launch and scale member banking experience products that build security awareness and adoption, keeping our members and Chime safe. Trust & Safety organization’s mission is to make Chime the most trusted financial partner by safeguarding member assets, ensuring regulatory excellence, and enhancing the tools and processes that protect our community, while delivering a seamless experience that works reliably for our members. Through experimentation, user behavioral analysis, sophisticated statistical and data science modeling, and dashboards development, you will surface product insights and recommendations that will increase engagement, and retention of our members.</span></p> <p><span style="font-family: helvetica, arial, sans-serif;">In this role, you will work closely with product managers, risk, engineers, product & lifecycle marketing, and operational stakeholders to foster a data-driven product development culture, advise our product roadmaps, and build a deep understanding of member behavior.</span></p> <p><span style="font-family: helvetica, arial, sans-serif;">The base salary offered for this role and level of experience will begin at $133,000 and up to $185,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.</span></p> <h2><span style="font-family: helvetica, arial, sans-serif;"><strong>In this role, you can expect to</strong></span></h2> <ul> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Partner widely with product, engineering, research, and design to translate your insights to guide product development. You’ll use data to help the organization understand how members are interacting with Chime and convert that to business and experience implications.</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Lead experimentation by providing mentorship on how they should be run, defining success metrics and data requirements, evaluating impact, and providing strategic direction.</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Drive roadmap, analysis and metric ideation, and strategi

<h2><span style="font-family: helvetica, arial, sans-serif;"><strong>About the role</strong></span></h2> <p><span style="font-family: helvetica, arial, sans-serif;">As a Sr. Spending Product Data Scientist, you will have the opportunity to develop, test, launch and scale member banking experience products that build products that make Chime banking the best place to spend, save and invest. Spending XFN organization’s mission is to deliver industry-leading spending products that members want to keep top of wallet. Our spending products help our members spend and manage their money, offering unmatched simplicity, rewards, and tools that bring them financial progress. Through experimentation, user behavioral analysis, sophisticated statistical and data science modeling, and dashboards development, you will surface product insights and recommendations that will increase engagement, and retention of our members.</span></p> <p><span style="font-family: helvetica, arial, sans-serif;">In this role, you will work closely with product managers, risk, engineers, product & lifecycle marketing, and operational stakeholders to foster a data-driven product development culture, advise our product roadmaps, and build a deep understanding of member behavior.</span></p> <p><span style="font-family: helvetica, arial, sans-serif;">The base salary offered for this role and level of experience will begin at $133,000 and up to $185,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.</span></p> <h2><span style="font-family: helvetica, arial, sans-serif;"><strong>In this role, you can expect to</strong></span></h2> <ul> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Partner widely with product, engineering, research, and design to translate your insights to guide product development. You’ll use data to help the organization understand how members are interacting with Chime and convert that to business and experience implications.</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Lead experimentation by providing mentorship on how they should be run, defining success metrics and data requirements, evaluating impact, and providing strategic direction.</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Drive roadmap, analysis and metric ideation, and strategic discussions with stakeholder

<h2><span style="font-family: helvetica, arial, sans-serif;"><strong>About the role</strong></span></h2> <p class="p2">We're looking for a Growth Product Scientist to partner with our Growth Product and Engineering teams to drive measurable impact across the member journey — from acquisition to conversion through long-term retention. You'll turn data into the decisions that shape how millions of members discover, direct deposit, and get value from Chime.</p> <p class="p2">This role sits at the intersection of product, data, and experimentation. You'll own funnels end-to-end, design and analyze A/B tests, and translate ambiguous business questions into clear, prioritized recommendations that ship.</p> <p class="p3">In this role, you will work closely with product managers, design, engineers, product & lifecycle marketing, and operational stakeholders to foster a data-driven product development culture, advise our product roadmaps, and build a deep understanding of member behavior.</p> <p class="p3">The base salary offered for this role and level of experience will begin at $109,000 and go up to $150,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.</p> <h2><span style="font-family: helvetica, arial, sans-serif;"><strong>In this role, you can expect to</strong></span></h2> <ul class="ul1"> <li class="li3">Partner with Product Managers, Engineers, Designers, and Marketers on growth initiatives spanning acquisition, onboarding, activation, and retention</li> <li class="li3">Design, run, and analyze A/B tests to improve member product experiences, including metric creation, experiment design, power analysis, and analysis of experiment results.; develop frameworks to prioritize the highest-leverage experiments</li> <li class="li3">Drive data-informed decision making within Growth org by equipping PMs and engineers with self-service analytics tools, and conducting ad hoc analyses and causal studies for the team.<span class="Apple-converted-space"> </span></li> <li class="li3">Use advanced statistical methods for causal inference, as well as time-series and other forecasting techniques, to solve product questions for the team. Occasionally apply machine learning methods for problems such as customer segmentation.<span class="Apple-converted-space"> </span></li> <li class="li3">Build and maintain dashboards, KPIs, and self-serve tooling that give the team a clear view of funnel health</li> <li class="li3&quo

Senior Data Scientist, B2B Product - San Francisco at Plaud. Apply via Ashby.

Data Scientist, B2B Growth - San Francisco at Plaud. Apply via Ashby.

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p> Data Science is at the heart of Lyft's products and decision-making. As a member of the Science team, you will work in a dynamic environment where we embrace moving quickly to build the world's best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products.</p> <p>As a Staff Data Scientist, Decisions on the Partnership, Loyalty & Pay (PLP) team within Rider, you will leverage data and apply analytical thinking and causal inference to shape our rider and partner product vision, and make business decisions that put our customers first. You will identify improvement opportunities, propose and implement technical solutions, design experiments, and measure the impact of your team's decisions. You will partner closely with product, engineering, design, research, marketing, and business development to deliver programs end-to-end. You will also collaborate and build alignment with adjacent teams across Rider, Marketplace, and Finance to balance driver, rider, and business needs.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Drive the data science roadmap across the Partnership, Loyalty, and Pay teams. Be a primary participant in defining team goals and setting the priorities of projects for the team to address</li> <li>Partner with org leads in product, engineering, UX research, design, marketing, and business development to initiate, design, develop, and scale zero-to-one programs and drive business strategy through data-centric recommendations</li> <li>Define and maintain key objectives and metrics to align with the overarching goals of Rider, Marketplace, and Lyft - including incrementality measurement for partnerships, retention impact of loyalty programs, and health of Pay products</li> <li>Apply modeling, advanced analytics, experimentation, and causal inference techniques (e.g., A/B testing, difference-in-differences, synthetic control, quasi-experimental methods) to drive decision-making at Lyft</li> <li>Drive cross-org impact and alignment, shaping product and business strategy through data-centric presentations to VP and C-level stakeholders</li> <li>Advise teams on best practices. Be a thought leader and go-to expert on measurement, incrementality, and causal inference for PLP stakeholders and dependency teams</li> <li>Provide technical guidance and mentorship to junior and mid-level team members on solution design and implementation; lead code reviews and elevate team-wide technical standards</li> </ul> <h2><strong>Experience:</strong>&

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p> The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products.</p> <p>As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems.</li> <li>Own complex domains and develop long-term roadmaps to maximize business impact.</li> <li>Build statistical pipelines, write production code, and design/analyze experiments.</li> <li>Participate in the science on-call rotation to ensure automated campaigns operate successfully.</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li>Advanced degree in statistics, economics, mathematics, or equivalent industry experience.</li> <li>4+ years of industry experience in causal inference or data science.</li> <li>Proven ability to apply statistics to unstructured problems and deliver measurable results.</li> <li>Deep technical expertise in causal inference and tackling challenging measurement problems.</li> <li>Expertise in marketing mix modeling is highly preferred.</li> <li>Expertise in SQL and experience with large-scale data platforms.</li> <li>Proficiency in Python and working within production coding environments.</li> </ul> <h2><strong>Benefits:</strong><strong><br></strong></h2> <ul> <li>Great medical, dental, and vision insurance options with additional programs available when enrolled</li> <li>Mental health benefits</li> <li>Family building benefits</li> <li>Child care and pet benefits</li> <li>401(k) plan with company match to help save for your future</li> <li>In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off</li> <li>18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible</li> <li>Subsidized commuter benefits</li> <li>Monthly Lyft credits and complimentary Lyft Pink membership</li> </ul> <p>Lyft is an equal opportunity employer comm

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p>Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features.</p> <p>As a Data Scientist on the Risk Solutions team, you will drive a mission critical to both the safety of our community and the financial resilience of our platform. You’ll partner cross-functionally with Product, Engineering, Actuarial and Claims teams to transform complex data into actionable strategies. You will serve as an analytical lead for claims and road safety initiatives, designing experiments and predictive models aimed at reducing accident frequency and claim severity to optimize long-term risk outcomes. If you are a problem-solver eager to apply high-level data science to real-world safety and financial challenges, this role offers a direct path to high-impact innovation.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Leverage large-scale data and analytic frameworks to identify high-impact opportunities to reduce the total cost of claims. </li> <li>Partner with product managers, engineers, actuaries, claims, and operators to translate data insights into decisions and action</li> <li>Construct and fit statistical, machine learning, or optimization models</li> <li>Design and analyze online experiments; communicate results and act on launch decisions</li> <li>Develop analytical frameworks to monitor business and product performance</li> <li>Establish metrics that measure the health of our products, the business, as well as the driver experience</li> <li>Collaborate with the Claims team to identify high-impact opportunities where data-driven interventions can reduce the total cost of claims.</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li>Degree in a quantitative field such as statistics, actuarial science, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience</li> <li>5+ years of industry experience in a data science, analytics, or management consulting role.  </li> <li>End-to-end experience with data, including querying, aggregation, analysis, and visualization</li> <li>Ability to manage, influence, negotiate, and inspire others in a fast-moving environment</li> <li>Proficiency in SQL and Python</li> <li>Experience with insurance

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p>The Rider team is the heartbeat of Lyft business. Every feature you build translates to a better experience for millions of riders globally. The Rider New Product team is the engine of innovation for Lyft's business. The Rider New Product science team’s mission is to rigorously quantify the value of innovation by applying advanced causal inference to unlock Lyft’s next generation of growth. You will have the autonomy of a startup lead with the data scale of a global tech giant.</p> <p>This is a high-impact, highly technical role within a core business line. The ideal candidate brings strong applied causal inference intuition, hands-on experience with advanced measurement techniques, and the ability to write clean, efficient production code. You will play a critical role in shaping the future of the Lyft rideshare experience by rigorously measuring the true incremental impact of new product features, shaping critical business decisions, and bridging the gap between cutting-edge applied science research and production-scale product impact.</p> <h2><strong>Responsibilities</strong></h2> <ul> <li>Own complex, open-ended incrementality measurement problems. Translate ambiguous product launches into concrete causal frameworks and experimental designs.</li> <li>Lead high-impact Causal Inference initiatives. Drive innovation by introducing advanced measurement techniques to quantify the incremental impact of new rider features.</li> <li>Partner deeply with Product, Engineering, and Finance. Define the technical vision for how Lyft evaluates innovation, ensuring that we move beyond simple correlations to understand the long-term drivers of rider behavior and value.</li> <li>Design and build production-grade measurement systems. Develop and deploy robust causal models pipelines that balance high scientific rigor with the practical constraints.</li> <li>Establish robust evaluation frameworks. Ensure that the "engine of innovation" is steering the business toward sustainable, incremental growth.</li> <li>Build reusable science infrastructure. Create internal libraries and best practices for causal discovery and automated measurement.</li> <li>Mentor and guide junior/mid-level scientists. Serve as a technical advisor on experimental design, statistical modeling, and fostering a culture of scientific excellence.</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li>Advanced Quantitative Background: Master’s or PhD in Economics, Statistics, Applied Math, Computer Science or equivalent high-impact industry experience.</li> <li>3+ Years of Applied Experience: Proven tra

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p>The Central Market Management & AI (CMM&AI) team, a key part of the broader Rideshare Experience & Marketplace organization, is essential for maintaining a balanced and efficient marketplace. We do so by developing foundational models, business datasets, and decision-making applications that support a wide range of teams across Lyft. These critical platforms and tools power our pricing / pay strategy, operational alignment, and regional strategies, enabling us to compete effectively in the Rideshare landscape.</p> <p>Data Scientists in CMM&AI solve the foundational problems that drive Lyft’s marketplace. From forecasting supply and demand to optimizing investments and measuring the ROI of growth levers, our work shapes both automated processes and high-level strategic decisions. Because our challenges are unique to a real-time marketplace, we avoid off-the-shelf solutions in favor of creativity and first-principles mathematical reasoning. We leverage a deep stack of technologies across forecasting, machine learning, inference, and optimization to deliver measurable impact.</p> <p>As a Senior Data Scientist on the Foundational Models team in CMM&AI, you will operate at the intersection of Machine Learning, Data Science, and Economics to build scalable optimization and modeling systems that directly impact Lyft’s top and bottom lines. You will be hands-on with formulating optimization problems, building ML models, productionizing pipelines, and integrating their outputs within decision-making frameworks. You will collaborate with Product, Engineers, Data Scientists, and Analysts to help define the roadmap and architecture for our next generation of foundational marketplace models that accelerate iterations and drive business efficiency.</p> <h2>Responsibilities:</h2> <ul> <li><strong style="font-size: 14px;">Optimization & Modeling</strong> <ul> <li>Design, formulate, and solve complex mathematical optimization problems that power Lyft’s marketplace decisions across pricing, pay, incentives, and resource allocation.</li> <li>Build, deploy, and maintain production-grade ML and optimization models; collaborate with Software Engineering to integrate algorithms into live systems and establish robust monitoring for model performance and data health.</li> <li>Own the full model lifecycle—from problem framing and prototyping through experimental validation and production deployment—refusing a “build and forget” mentality.</li> <li>Apply first-principles mathematical reasoning to marketplace challenges, choosing the simplest effective solution and building complexity only when incremental value

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p>Data Science is central to Lyft's products and decision-making. As a Data Scientist on the cross-functional team, you will work in a dynamic environment, tackling a variety of problems from shaping critical business decisions to building algorithms that power our products. We seek passionate, driven Data Scientists to address some of the most interesting and impactful problems in ridesharing.</p> <p>As a Data Scientist specializing in Algorithms, you will develop mathematical models for the platform's core services, addressing diverse problems in optimization, prediction, machine learning, and inference. On the Fulfillment team, you will collaborate with cross-functional teammates and stakeholders to enhance algorithms for matching rideshare supply and demand in real time and develop product offerings to improve the experiences of Lyft Riders and Drivers.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team’s systems and products</li> <li>Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.</li> <li>Perform exploratory data analysis to gain a deeper understanding of the problem</li> <li>Construct and fit statistical, machine learning, or optimization models</li> <li>Write production modeling code; collaborate with Software Engineers to implement algorithms in production</li> <li>Design and implement both simulated and live traffic experiments</li> <li>Analyze experimental and observational data; communicate findings; facilitate launch decisions</li> <li>Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes</li> <li>Drive collaboration and coordination with cross-functional teams</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li>M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields</li> <li>2+ years professional experience in a technology company setting</li> <li>Proven experience with building and evaluating machine learning models</li> <li>Proficiency with Python and working in a production coding environment</li> <li>Passion for solving unstructured and non-standard mathematical problems</li> <li>End-to-end experience with data, including querying, aggregation, analysis, and visualization</li> <li>Strong oral a

Data Scientist, GTM at Cursor. Apply via Ashby.