Data Scientist, Strategic Intelligence & Risk

About Our TeamThe Intelligence and Investigations team at OpenAI is committed to proactively identifying and mitigating online abuse and strategic risks. Our mission is to foster a safe digital ecosystem by analyzing emerging trends and collaborating with internal and external partners to implement effective measures against misuse. Through our initiatives, we contribute to OpenAI's goal of creating AI technologies that enhance human well-being.The Strategic Intelligence & Analysis (SIA) team specializes in providing safety intelligence for OpenAI’s products. By monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats, we guide safety measures, product strategies, and partnerships. Our work ensures that OpenAI’s tools are utilized securely and responsibly in essential sectors.About the RoleAs a Data Scientist, you will spearhead econometric and experimental analyses to comprehend risk dynamics within complex human–AI systems. Your focus will be on quantifying the magnitude and implications of risk fluctuations in a fast-paced, evolving environment. You will design experimental and observational studies to uncover causal factors and assess risk changes across diverse surfaces and sources. Your insights will directly influence strategic risk management and prioritization across the organization.This position is based in San Francisco, CA (hybrid, 3 days/week) with relocation assistance available.Key Responsibilities:Design and execute experimental and observational analyses to evaluate strategic risks.Develop econometric models to assess the impact of product, policy, and external factors on critical risk vectors.Translate strategic risk inquiries into testable hypotheses and robust study frameworks.Implement A/B tests and pseudo-experimental studies to measure risk changes and uncover underlying mechanisms.Identify, test, and clarify product-driven, event-driven, or signal-driven risk variations.Establish baselines and statistical confidence around core metrics to define the scale of risks.Collaborate across teams to monitor strategic risks, pinpoint intervention opportunities, and assess the effectiveness of those interventions.

Join Whatnot as a Data Scientist specializing in Risk & Fraud and leverage your analytical skills to help us combat fraud and mitigate risks in our vibrant online marketplace. You will work collaboratively with cross-functional teams to analyze data, identify trends, and develop strategies that improve our platform's security and user experience.

About Owner.comOwner.com is revolutionizing the growth trajectory of local restaurants through advanced AI technology.Our AI solutions are meticulously designed to enhance SEO, marketing strategies, and online ordering processes, ultimately boosting first-party orders. Unlike other companies that burden small business owners with complex software, Owner.com provides a streamlined, expert-driven system that guarantees results.Think of us as your dedicated team of engineers and marketers, empowering independent restaurants to compete with larger chains.Our VisionInitially focused on helping independent restaurants thrive online, our mission extends to all local businesses facing similar challenges.In an era where massive tech corporations threaten local business survival, we are committed to leveling the playing field.Once we perfect our solutions for restaurants, our goal is to expand our services across various local business sectors.We envision a future where millions of local business owners leverage our technology to excel in the digital landscape.Discover our Series C memo here →Our TractionSince our inception in 2020, we have generated tens of millions in revenue and processed over half a billion dollars in online orders. One in five Americans has interacted with an Owner.com website.More significantly, we have supported over 20,000 restaurant owners, saving them close to $200 million in fees.Our TeamOur dynamic team, composed of top talent from renowned companies in the SMB software space, is poised for rapid expansion as we continue to grow alongside our customers.

Join fal as a Senior Data Scientist specializing in Product Intelligence, where you will design the analytical architecture that drives our growth. Your expertise will encompass the entire developer journey, from initial acquisition to sustained expansion. You will transform raw behavioral and system signals into actionable metrics and insights that guide our product strategy and market approach.This strategic position allows you to collaborate closely with teams in Product, Engineering, and Marketing. You will not only conduct domain-specific analyses but also take ownership of the foundational data systems, standards, and experimentation frameworks that provide essential insights across the company.

Join Airwallex as a Senior Data Scientist in Risk & FraudAt Airwallex, we are redefining the future of global payments and finance. As a Senior Data Scientist specializing in algorithms for risk and fraud prevention, you will be an integral part of our innovative team, working to safeguard transactions for over 200,000 businesses worldwide.Your expertise will help us build advanced machine learning models that address the ever-evolving challenges of fraud. You'll collaborate with a team of brilliant minds in a fast-paced environment, leveraging cutting-edge technology to develop solutions that are not just effective but also transformative.Join us in our mission to create a seamless financial experience for businesses globally!

About Our TeamJoin the Intelligence and Investigations team at OpenAI, where we are committed to swiftly identifying and addressing abuse and strategic risks to foster a secure online environment. We focus on uncovering emerging abuse patterns, assessing risks, and collaborating with both internal and external stakeholders to implement effective strategies that prevent misuse. Our mission aligns with OpenAI's broader vision of creating AI technology that serves humanity positively.We are developing a comprehensive “radar” for AI abuse and strategic risk—integrating internal signals, external insights, and real-world occurrences into actionable priorities for OpenAI’s safety and product development teams.About the PositionAs a Strategic Risk Analyst specializing in Behavioral & Psychological Risk, you will leverage your extensive knowledge of human behavior to provide a holistic view of risk across OpenAI’s products and platforms.Your role involves analyzing user interactions with AI systems, particularly in high-stakes situations such as self-harm, manipulation, and coercion, and translating these findings into ready-to-use risk assessments, mitigation strategies, and product insights.This position merges clinical and behavioral expertise with intelligence analysis, transforming psychological indicators and trends into structured evaluations, early warnings, and actionable recommendations. A significant aspect of your work will be to proactively identify where analytical insights are crucial, anticipate emerging product, policy, and safety inquiries, and concentrate efforts on analyses that influence critical decisions.You will collaborate closely with investigators, engineers, policy experts, and trust & safety teams to enhance our understanding and mitigation of potential risks in human-AI interaction.Key ResponsibilitiesAnalyze AI system usage in complex or high-risk contexts (e.g., self-harm, suicidal thoughts, substance use escalation, and threats of violence), identifying patterns and trends that inform product, safety, and policy strategies.Integrate behavioral, psychological, and intelligence signals into coherent narratives that elucidate user needs, system dynamics, and potential vulnerabilities.Create decision-ready briefs and assessments to support product, safety, and policy decisions.Develop and enhance behavioral risk frameworks, taxonomies, and indicators (e.g., severity models, escalation pathways, psychological harm classifications).

Join Our Dynamic TeamAt OpenAI, the Strategic Finance team plays a pivotal role in driving substantial investment initiatives. We are dedicated to enhancing OpenAI's long-term success by collaborating across departments to strategically allocate resources for maximum impact. Our team works closely with Finance, Product, Engineering, and Go-To-Market divisions to provide critical insights and support strategic decisions that shape the future of our company.Your Role and ResponsibilitiesAs a key member of the Strategic Finance Data Science team, you will be instrumental in designing, developing, and managing essential models, reporting systems, and analytical frameworks. Collaborating with Finance leadership and interdisciplinary teams, you will leverage your expertise in predictive modeling and causal inference to deliver actionable insights that inform high-stakes decision-making.This position is based at our San Francisco headquarters, adopting a hybrid work model with three days in the office each week. We also offer relocation assistance to new hires.Your Key Contributions Will Include:Deeply understanding OpenAI’s data architecture and collaborating with Data Engineering and Finance teams to extract valuable insights.Developing and scaling causal inference models to evaluate the effects of various strategies on user growth and financial performance.Creating customer segmentation strategies to drive targeted growth initiatives and enhance customer lifetime value.Automating reporting and analyses through innovative data products and agentic solutions.Conducting ad hoc analyses to support product pricing and other key business decisions.Designing and presenting dashboards that empower leadership to monitor key performance indicators and make informed decisions.Leading cross-functional data science projects from inception to completion, ensuring timely and impactful delivery.Ideal Candidate Profile:Master's or PhD in a quantitative discipline, with a minimum of 7 years of experience in a data-centric role, preferably in a fast-paced, high-growth environment.Proficient in Python, SQL, Tableau, and other analytical tools.Strong analytical prowess with experience in managing and interpreting large, intricate datasets.Proven ability to translate complex data into clear, actionable insights.

About the TeamThe Intelligence and Investigations team is committed to swiftly identifying and mitigating strategic risks and abuse to foster a secure online environment. Our mission focuses on uncovering emerging abuse trends, analyzing risks, and collaborating with internal and external partners to enforce effective mitigation strategies that protect against misuse. These efforts are vital to OpenAI's overarching goal of creating AI that serves humanity.We aim to establish a comprehensive “radar” for AI abuse and strategic risks—integrating internal signals, external intelligence, and real-world events to generate clear, actionable priorities for OpenAI’s safety and product decision-makers.About the RoleAs a Strategic Risk Analyst, you will play a pivotal role in developing and maintaining a centralized perspective on strategic risk across OpenAI's products and platforms. Your responsibilities will include synthesizing internal abuse patterns, external intelligence, and product signals into actionable risk insights, regular briefs, and practical prioritization inputs.You will collaborate closely with investigators, engineers, policy and trust and safety counterparts, as well as measurement and forecasting teams to convert complex signals into structured judgments, ranked priorities, and actionable recommendations. This position offers an opportunity to conduct high-impact analysis in a dynamic environment, where clear thinking and communication will directly influence safety decisions, mitigations, and product readiness.In This Role, You WillMonitor and analyze internal risk signals (abuse telemetry, investigation outputs, model and product signals) to identify trends, tactical shifts, and new abuse patterns.Conduct upstream and external scanning (OSINT, ecosystem developments, real-world events) and distill implications for OpenAI’s products and threat landscape.Identify and thoroughly investigate harms and misuse across products and channels, transforming complex signals into clear analytical findings.Connect individual incidents into overarching narratives about actors, incentives, product design vulnerabilities, and cross-product spillover, while pressure-testing hypotheses early in the analysis.Produce concise, decision-ready risk briefs and intelligence assessments that include explicit assumptions, confidence levels, and factors that could alter the evaluation.Translate analysis into clear, ranked priorities and actionable recommendations that product, safety, and policy teams can implement effectively.

About Matter IntelligenceMatter Intelligence is at the forefront of Vision AI innovation, developing a groundbreaking sensor capable of interpreting molecular chemistry, temperature, and 3D shapes, all powered by an advanced Large World Model. This revolutionary system not only captures visual data but comprehensively understands the nuances behind each pixel. We call it Superintelligent Vision.Join a remarkable team with a proven track record, having delivered technologies to NASA/JPL for Mars missions, co-founding and building infrastructure for OpenAI, crafting state-of-the-art sensors for U.S. Defense, and developing pivotal algorithms for spectral and 3D imaging. Together, we are laying the groundwork for the next generation of vision and intelligence in our physical world.About the RoleWe are seeking a passionate Junior Geospatial Data Scientist to design and sustain processing pipelines and algorithms that convert our satellite's raw hyperspectral imagery into high-quality scientific data products. This role is not solely research-oriented; you will be responsible for writing production-level code that operates at scale, and a solid understanding of the mathematics and physics behind each pipeline component is essential.In collaboration with experienced remote sensing scientists and software engineers, you will execute radiometric corrections, atmospheric compensation, spectral analysis algorithms, and geospatial data transformations. If you have the ability to derive a reflectance equation on a whiteboard and seamlessly translate it into a clean, tested Python module, this opportunity is perfect for you.

Join Lyft as a Senior Data Scientist specializing in Risk Analysis, where you will leverage advanced analytics and machine learning to drive decision-making processes. Collaborate with cross-functional teams to develop innovative risk assessment models that enhance our service offerings and ensure safety for our users. Your expertise will play a crucial role in shaping our data-driven strategies.

Employee Applicant Privacy NoticeAbout Us:Join us in shaping a brighter financial future. At SoFi, we are revolutionizing the way individuals engage with personal finance through innovative, mobile-first technology. As a next-generation financial services company and national bank, we are committed to helping our millions of members achieve their financial goals. With a rapidly evolving industry, we are proud to be at the forefront of this transformation. Our core values drive us to make a meaningful impact on people’s lives every day. Invest in yourself, your career, and the financial world by joining our team!The Role:The Risk Data Science team is on the lookout for a strategic and technically proficient Machine Learning Engineer to spearhead the advancement of SoFi’s Home Loan and Home Equity risk frameworks. This pivotal role is part of a high-priority initiative aimed at delivering a comprehensive, loan-level credit risk and valuation framework for our home lending portfolios.As a key technical leader, you will harness cutting-edge ML methodologies to tackle complex challenges, including default and prepayment modeling, property valuation (AVMs), and credit risk assessment, ensuring our valuable secured loan products are underpinned by top-tier data science.Your Responsibilities:Lead the development and implementation of ML models tailored for mortgage-specific applications, such as credit underwriting, debt-to-income (DTI) validation, and automated appraisal reviews.Oversee the technical evaluation and comprehensive ownership of externally developed models, ensuring adherence to stringent internal standards for quality, performance, and scalability.Communicate model performance and portfolio insights to senior leadership, translating intricate data into actionable credit and business strategies.Collaborate with Model Risk Management (MRM) and governance teams to guarantee that all models are developed with the technical rigor necessary to meet complex regulatory and compliance requirements.Work alongside Product and Engineering teams to operationalize models, overseeing their deployment, real-time monitoring, and seamless integration into core business systems.Continuously explore and utilize in-house, external, and open-source ML frameworks to create the next generation of proprietary mortgage risk tools.

Join the dynamic Analytics team at DoorDash as a Data Scientist or Senior Data Scientist, where your expertise will directly influence strategic decisions and operational improvements. You will uncover valuable insights from vast datasets, transforming them into actionable recommendations that drive company-wide initiatives. Collaborate with diverse teams in areas like Consumer & Growth, Business Operations, and Customer Experience to elevate our analytics capabilities and impact our business in meaningful ways.

About Our TeamThe Intelligence and Investigations team is dedicated to swiftly identifying and mitigating abuse and strategic risks, ensuring a secure online environment through close collaboration with both internal and external partners. Our initiatives align with OpenAI's fundamental mission of developing AI technologies that benefit humanity.The Strategic Intelligence & Analysis (SIA) team plays a crucial role in providing safety intelligence for OpenAI’s products. We focus on monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring that OpenAI’s tools are deployed securely and responsibly across critical sectors.About the RoleWe are in search of an AI Emerging Risks Analyst who will aid in comprehending potential harms and misuse of AI in a landscape characterized by rapid and sustained changes. This role involves identifying known threat actors who exploit new technologies as well as emerging threats enabled by these advancements. You will utilize strategic foresight methodologies to proactively detect and mitigate risks.In this position, you will provide a strategic-level perspective on a diverse range of evolving risk areas. You will be instrumental in creating actionable risk taxonomies pertinent to OpenAI’s platforms and broader business interests. By employing both quantitative and qualitative methodologies, you will identify early warning signals, investigate concerning behaviors, and transform weak signals into prioritized risk assessments. Your focus will include upstream ecosystem scanning, competitive benchmarking, and external narrative/risk sense-making. Your contributions will guide cross-functional partners in the protection and safety domains, ensuring user, brand, and community safety while fostering productive and creative uses of our tools.Key ResponsibilitiesIdentify and prioritize emerging risksDevelop and continuously refine a comprehensive view of emerging signals and trends that may impact the AI ecosystem through proactive scanning.Design and maintain harm taxonomies to foresee and warn about potential AI-related harms and misuse over the next 0-24 months and beyond.Contribute to an ongoing risk register and prioritization framework that highlights the most pressing issues based on severity, prevalence, exposure, and trajectory.Analyze and delve into emerging abuse patternsCreate thorough strategies to investigate and understand these patterns.

At Databricks, our passion lies in empowering data teams to tackle some of the most challenging problems globally, from detecting security threats to advancing cancer drug development. We achieve this by creating and operating the world's premier Data Intelligence Platform, enabling our customers to concentrate on high-value challenges central to their missions. Founded in 2013 by the original creators of Apache Spark, Databricks has evolved from a small office in Berkeley, California, into a global powerhouse with over 1000 employees. We are trusted by thousands of organizations—from small startups to Fortune 100 companies—with their mission-critical workloads, establishing us as one of the fastest-growing SaaS companies worldwide. Our engineering teams are dedicated to developing highly technical products that address real-world needs. We continuously push the limits of data and AI technology while maintaining the resilience, security, and scalability crucial for our customers' success on our platform. Operating one of the largest-scale software platforms, our infrastructure comprises millions of virtual machines that generate terabytes of logs and process exabytes of data daily. At this scale, we routinely encounter cloud hardware, network, and operating system faults, and our software is designed to shield our customers from such issues effectively. As a Data Scientist on the Data Team, you will play a pivotal role in fostering a data-driven culture within Databricks by addressing product and business challenges. The Data Team serves as an internal, production 'customer' that utilizes Databricks and influences the future trajectory of our products. Your Impact: Steer the direction of key data science initiatives including segmentation, recommendation systems, forecasting, product analytics, churn prediction, and insights. Collaborate closely with Engineering, Product Management, Sales, and Customer Success to discern product usage patterns and trends, facilitating data-driven decisions, recommendations, and forecasts. Manage stakeholder expectations in your focus area—gather evolving requirements, define project OKRs and milestones, and effectively communicate progress and results to non-technical audiences. Mentor and support junior data scientists within the team, assisting with project planning, technical decisions, and conducting code and documentation reviews. Advocate for the data science discipline across the organization, amplifying our commitment to becoming more data-driven. Develop self-service internal data products to simplify data access within the company. Represent Databricks at academic and industry conferences and events.

SentiLink is at the forefront of revolutionizing identity verification and risk solutions, enabling organizations and individuals to conduct transactions with utmost confidence. Our mission is to redefine the identity verification landscape in the United States by delivering solutions that outpace traditional methods in speed, intelligence, and accuracy.With significant growth momentum, SentiLink's real-time APIs have successfully validated hundreds of millions of identities, initially within financial services and rapidly branching into diverse sectors. We are proudly supported by esteemed investors such as Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.Our innovative approach has garnered accolades from industry leaders and media outlets, including TechCrunch, CNBC, Bloomberg, Forbes, and Business Insider. Notably, we have consistently secured a spot on the Forbes Fintech 50 list since 2023. We also made history by being the first company to launch the eCBSV and by presenting our insights to the United States House of Representatives regarding the future of identity.SentiLink embraces various work arrangements, from fully remote to on-site options. As a digital-first organization, we foster robust collaboration across teams in the U.S. and India, with physical offices located in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., along with Gurugram and Bengaluru in India. For those near our offices, we encourage regular in-office engagement, although some roles are intentionally hybrid or office-based, exemplified by our engineering team in India who primarily operates from our Gurugram office.

About Matter IntelligenceWelcome to Matter, a pioneering company at the forefront of vision AI. We are developing an unprecedented sensor capable of perceiving molecular chemistry, temperature, and 3D structure, integrated with a Large World Model that serves as the most advanced intelligence engine for our physical environment. Our unique system not only captures visual data but also comprehends intricate details from a single pixel—what we refer to as Superintelligent Vision.Join a team with an impressive track record, having provided technologies for NASA/JPL's Mars missions, co-founding and spearheading infrastructure for OpenAI, and crafting state-of-the-art sensors for U.S. Defense. Our collective expertise is dedicated to creating the next generation of infrastructure for vision and intelligence in the physical realm.About the RoleWe are in search of a Senior Geospatial Scientist to spearhead the development of sophisticated algorithms and data pipelines that convert our ultraspectral imagery into actionable insights. This pivotal role merges remote sensing science, machine learning, and scalable cloud infrastructure, effectively transforming raw hyperspectral data into validated, production-ready data products.Your responsibilities will include designing and implementing physics-informed machine learning algorithms, constructing robust AWS-based processing pipelines, and ensuring the scientific integrity of each output—from the sensor physics to the final data products. Your contributions will directly empower Matter's mission to deliver transformative Earth observation capabilities across various industries.Key ResponsibilitiesAlgorithm DevelopmentDesign and implement machine learning (ML) and physics-informed algorithms for hyperspectral data analysis.Develop spectral unmixing, classification, and regression models tailored to diverse geospatial applications.Translate domain-specific science (agriculture, mineralogy, ecology, aquatics) into validated algorithmic methodologies.Utilize modern AI tools to enhance code generation and accelerate problem-solving.Pipeline ArchitectureConstruct and maintain scalable data processing pipelines on AWS for handling extensive geospatial datasets.Architect systems for radiometric correction, atmospheric compensation, and geometric orthorectification.Optimize processing pipelines for efficiency in throughput, latency, and cost management across petabyte-scale imagery.

Northbeam creates a marketing intelligence platform designed for eCommerce brands. The platform helps clients track ad spend, map the customer journey, and make informed decisions for business growth. Brands use Northbeam’s advanced attribution models and customizable dashboards to gain a clear understanding of their data. The company has established strong product-market fit and is expanding quickly. Northbeam values individual growth, high standards, and teamwork. While the company operates fully remote across the US, offices in San Francisco and Los Angeles are available for those who prefer in-person work. Role overview The Staff Data Scientist will play a central role in advancing the statistical and experimental foundations of Northbeam’s marketing intelligence products. This includes work on Media Mix Modeling (MMM), Incrementality, Insights, and Recommendation engines. The position covers the full data science workflow: researching and developing statistical methods, applying causal inference, deploying models, and maintaining production systems. This role bridges R&D and product, with responsibilities that span from data exploration and experimental design to validation and integration of models into production. A deep understanding of statistical modeling and the underlying assumptions is critical. The work involves adapting and stress-testing models for real-world marketing data, which often diverges from textbook scenarios. The position offers significant autonomy and requires hands-on technical work, frequent collaboration with other teams, and a focus on solving customer problems as business priorities evolve. What you will do Develop and refine statistical modeling methods for marketing intelligence applications Collaborate with teams across Northbeam to improve product features Deliver actionable insights through detailed analysis Requirements Expertise in statistical modeling and causal inference Experience designing and validating models for production systems Ability to adapt modeling approaches to complex, real-world data Comfort working both independently and as part of a collaborative team

Join Arena Intelligence as a Data ScientistArena Intelligence stands at the forefront of AI evaluation, offering an open platform that examines how AI models perform in real-world scenarios. Founded by UC Berkeley's SkyLab researchers, our mission is to push the boundaries of AI utility.Each month, millions engage with Arena Intelligence to assess the performance of pioneering AI systems, using our community's insights to foster transparent, comprehensive, and human-centric model evaluations. Leading enterprises and AI labs depend on our evaluations to gauge real-world reliability, alignment, and impact. Our leaderboards are regarded as the benchmark for AI performance, trusted by industry leaders and influencing global discussions on model reliability and advancement.Our diverse team of researchers, engineers, and builders hail from prestigious institutions such as UC Berkeley, Google, Stanford, DeepMind, and Discord. We prioritize truth, agility, and craftsmanship while fostering an environment that values curiosity and impact over hierarchy. At Arena, skilled individuals from all backgrounds are empowered to excel in their fields, contributing to an atmosphere rich in excellence, energy, and focus.The RoleAs a Data Scientist, you will investigate and interpret the data that fuels millions of AI evaluations weekly. Your responsibilities will include generating and testing hypotheses, identifying causal relationships, and revealing insights that enhance our understanding of frontier model behaviors in practical applications. You will collaborate with machine learning researchers and engineers to design experiments, analyze extensive datasets, and develop statistical frameworks aimed at refining the reliability and interpretability of our AI evaluation systems. Senior-level candidates are preferred for this role.

Samba TV is a cutting-edge AI-driven media intelligence firm dedicated to empowering marketers with comprehensive insights into their audiences. Our advanced AI technology analyzes media consumption across millions of smart TVs and 2.5 billion web pages, integrating this data with external signals through the Samba Knowledge Graph, which maps the genuine interests, behaviors, and purchasing intents of 1.5 billion global user profiles. Brands, agencies, publishers, and platforms leverage Samba's capabilities to enhance their decision-making processes throughout every phase of the marketing funnel.ABOUT THE ROLEWe are on the lookout for a proactive Data Scientist who will take charge of complex measurement science and modeling initiatives central to our measurement and audience science offerings. This position demands a profound, foundational understanding of data science and machine learning—beyond merely utilizing libraries; it requires the ability to think critically about model behavior, clearly communicate the trade-offs between different strategies, and make sound methodological choices amidst uncertainty. This role is primarily focused on coding; you will dedicate most of your time to writing high-quality Python code, constructing and assessing models based on extensive viewership and web data, and delivering comprehensive ML solutions.Collaboration with Data Engineering, Product, and go-to-market teams will be integral to your success.

Join our dynamic Analytics team at DoorDash, where we are seeking an innovative Senior Lead Data Scientist to spearhead the exploration and interpretation of complex data sets. This pivotal role will help shape our global platform expansion strategies, driving informed decisions across all facets of our organization.About the TeamThe Analytics team is dedicated to leveraging advanced analytical methodologies to inform strategic initiatives and operational decisions. As a Senior Lead Data Scientist, you will play a crucial role in transforming insights into actionable strategies that contribute to DoorDash’s success.About the RoleIn this role, you will delve into intricate data analyses to tackle significant business challenges, devise and implement experiments based on your findings, and collaborate with cross-functional teams to enact meaningful operational changes. Your expertise will be crucial in enhancing our marketplace efficiencies, optimizing customer acquisition, and addressing fraud prevention among other exciting challenges.If you thrive on identifying patterns in data chaos, possess a passion for building impactful market strategies from the ground up, and have a proven track record of employing analytics to drive revenue and operational growth, we want to hear from you!Your ImpactLead and mentor a team of Data Scientists in uncovering vital business insights while also contributing as an individual expert.Shape the Product and Operations roadmap with data-driven recommendations.Engage with senior leadership to present your team's findings and address complex business challenges.Establish measurement strategies for your area, defining key performance indicators and best practices in experimental design and statistical analysis.Craft a strategic learning roadmap informed by data insights, key questions, and hypotheses.QualificationsA Master’s or Ph.D. in Mathematics, Physics, Statistics, Economics, Computer Science, or a related field.8+ years of experience in Data Science, with a focus on product analytics and operational strategies.Proficiency in statistical tools and programming languages such as Python, R, or SQL.Strong analytical mindset with a demonstrated ability to solve complex problems using data.Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.