Data Scientist, People

About The CompanyDoorDash is a leading technology and logistics company dedicated to empowering local economies through innovative delivery solutions. Originating as a platform for door-to-door food delivery, the company has rapidly expanded its services to become a comprehensive platform for all goods, connecting consumers, merchants, and delivery partners seamlessly. With a focus on growth, innovation, and community impact, DoorDash strives to redefine the future of commerce by leveraging cutting-edge technology, data-driven insights, and a customer-centric approach. The organization values diversity, inclusion, and a collaborative culture, fostering an environment where employees are encouraged to share their perspectives, develop their careers, and contribute to meaningful change within the industry.About The RoleAs a Data Scientist within the People Data Science team at DoorDash, you will play a pivotal role in shaping the future of people analytics through advanced AI and large language model (LLM)-based solutions. Your primary responsibility will be to develop and deploy models that extract actionable insights from both quantitative and qualitative employee data, spanning the entire employee lifecycle from hiring to engagement and retention. This role requires a blend of expertise in statistical modeling, natural language processing (NLP), machine learning, and a deep understanding of organizational behavior and people analytics. You will collaborate closely with data engineers, applied scientists, and HR business partners to create scalable systems that help leadership make informed, data-driven decisions to foster a high-performing, engaged workforce. Your work will involve building intelligent tools that summarize employee sentiment, analyze open-ended feedback, and identify emerging trends, ultimately contributing to strategic initiatives aimed at improving organizational effectiveness and employee experience.QualificationsMaster’s or Ph.D. in Data Science, Computer Science, Statistics, Applied Mathematics, Economics, Industrial-Organizational Psychology (quantitative track), or a related field.3+ years of experience applying data science methods to real-world problems, with at least 1–2+ years in People Analytics preferred.Proficiency in Python and SQL, along with experience using machine learning and NLP libraries such as scikit-learn, statsmodels, PyTorch, TensorFlow, or Hugging Face Transformers.Proven experience building or applying large language models (LLMs) and NLP-based systems for tasks like text summarization, sentiment analysis, or insight extraction.Strong foundation in statistical modeling, causal inference, and experimental design, including regression, clustering, A/B testing, and time-series analysis.Experience designing, testing, and deploying scalable data pipelines using tools like Snowflake, dbt, and Databricks.Familiarity with LLM orchestration frameworks such as LangChain or LlamaIndex, and vector databases like Postgres with pgvector.Excellent communication skills with the ability to translate complex analyses into clear, actionable insights through visualization and storytelling.Experience creating dashboards and data visualizations using tools such as Tableau, Looker, or Sigma.A passion for developing ethical AI solutions that enhance organizational decision-making and employee experience.ResponsibilitiesDevelop AI-powered people analytics tools, including LLM- or agent-based systems that summarize employee sentiment, analyze qualitative feedback, and identify trends in organizational data.Apply advanced statistical and machine learning techniques to understand drivers of engagement, retention, and performance within the organization.Design, test, and implement scalable data models and pipelines capable of analyzing large volumes of survey, feedback, and HR data.Collaborate with cross-functional teams—including People, Engineering, and Product—to create AI solutions aligned with business strategies and organizational goals.Translate complex data findings into compelling narratives that inform leadership decisions and organizational priorities.Explore and implement cutting-edge NLP and Generative AI (GenAI) techniques, including embeddings, topic modeling, and fine-tuning of LLMs for people analytics applications.Contribute to the evolution of the People Data Science function, helping shape scalable, AI-driven insights that support the future of work.Maintain awareness of emerging trends in AI, NLP, and organizational research to continuously enhance analytics capabilities.BenefitsCompetitive salary within the range of $124,100 — $182,500 USD, based on skills and experience.Opportunities for equity grants and other performance-based incentives.Comprehensive health benefits including medical, dental, and vision coverage.401(k) plan with employer matching contributions.Paid parental leave—up to 16 weeks—and family-forming assistance.Paid time off, including flexible vacation and sick leave in accordance with local laws.Wellness benefits and mental health programs to support overall well-being.Paid holidays, disability, and basic life insurance coverage.Commuter benefits, flexible work arrangements, and ongoing professional development opportunities.Equal OpportunityDoorDash is committed to fostering an inclusive and diverse workplace. We ensure equal employment opportunities regardless of race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other protected category. We believe that a diverse workforce enhances our innovation, creativity, and ability to serve our communities effectively. We welcome applications from individuals of all backgrounds and experiences and are dedicated to providing accommodations for candidates with disabilities throughout the hiring process.