Data Scientist, People at DoorDash USA

Los Angeles, California, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Feb, 26

Salary

182500.0

Posted On

15 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Natural Language Processing, Statistical Modeling, Causal Inference, Experimental Design, Python, SQL, Large Language Models, Data Visualization, AI Solutions, People Analytics, Data Pipelines, Sentiment Analysis, Insight Extraction, Collaboration

Industry

Software Development

Description

About the Team The People Data Science team is part of DoorDash’s People Intelligence organization, a multidisciplinary group that combines data science, business intelligence, analytics engineering, and data engineering to power our people decisions with trusted, scalable insights. Together, we enable DoorDash to unlock the full potential of our talent and drive measurable improvements in organizational effectiveness. As the advanced analytics arm of People Intelligence, the People Data Science team applies statistical modeling, machine learning, and AI-driven analysis to uncover trends and patterns across the employee lifecycle — from hiring to engagement to retention. By transforming people data into meaningful insights, we help DoorDash foster a thriving, high-performing workforce and make data-informed decisions that elevate the employee experience and organizational impact. About the Role As a Data Scientist on the People Team at DoorDash, you will shape the future of people analytics by building and deploying AI and LLM-based models that deliver insights from both quantitative and qualitative employee data. You’ll design intelligent systems and agents that leverage large-scale employee experience, performance, and organizational data — integrating structured and unstructured signals to uncover trends that inform talent strategy and business outcomes. This role blends deep expertise in statistical modeling, natural language processing, and applied machine learning with a strong understanding of people analytics and business context. You’ll collaborate with data engineers, applied scientists, and People Business Partners to develop scalable insight-generation systems that help leaders make more informed, data-backed decisions. You're excited about this opportunity because you will... Build AI-powered people analytics tools — develop LLM- or agent-based systems that summarize employee sentiment, extract insights from qualitative feedback, and surface trends in quantitative data. Apply advanced statistical and ML techniques to understand drivers of engagement, retention, and performance. Design, test, and deploy scalable models and pipelines that analyze large volumes of survey, feedback, and HR data. Collaborate cross-functionally with People, Engineering, and Product partners to design AI solutions that support business strategy and improve the employee experience. Translate data into action — tell compelling stories with data that shape leadership decisions and organizational priorities. Explore cutting-edge GenAI and NLP approaches — from embeddings and topic modeling to fine-tuning LLMs for people analytics applications. Contribute to the evolution of People Data Science at DoorDash — shaping our approach to scalable, AI-driven insights for the future of work. We’re excited about you because you have... Master’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 (1–2+ years in People Analytics preferred). Proficiency in Python and SQL, with experience using ML and NLP libraries (e.g., scikit-learn, statsmodels). Proven experience building or applying large language models (LLMs) and NLP-based systems for text summarization, sentiment analysis, or insight extraction. Strong foundation in statistical modeling, causal inference, and experimental design (e.g., regression, clustering, A/B testing, time-series). Experience designing and scaling data pipelines using Snowflake, dbt, Databricks. Familiarity with LLM orchestration tools (e.g., LangChain, LlamaIndex, or similar frameworks) and vector databases (e.g., Postgres with pgvector). Ability to distill complex analyses into actionable insights through clear communication, visualization, and storytelling. Experience creating data visualizations and dashboards using tools such as Sigma, Tableau, or Looker to communicate insights effectively. Passion for building AI solutions that empower people leaders and improve organizational decision-making through ethical and responsible applications of data science. Nice-to-have Experience building or contributing to AI analytics assistants or chatbots that enable natural language access to insights. Experience with data science python packages such as PyTorch, TensorFlow, and Hugging Face Transformers. Experience in survey analytics, employee engagement research, or text analytics using large-scale feedback data. Familiarity with HRIS systems (e.g., Workday) and core workforce metrics such as attrition and engagement. Exposure to fine-tuning foundation models and evaluating LLM performance for reliability and bias. Experience with graph databases (e.g., Neo4j) for modeling organizational networks. Background in applied behavioral science, organizational research, or people analytics experimentation. Compensation The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information. DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others. To learn more about our benefits, visit our careers page here. See below for paid time off details: For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week). The national base pay range for this position within the United States, including Illinois and Colorado. $124,100—$182,500 USD About DoorDash At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more. Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination. Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation. If you need any accommodations, please inform your recruiting contact upon initial connection.

Responsibilities

As a Data Scientist on the People Team, you will build and deploy AI and LLM-based models to derive insights from employee data. You will collaborate with various teams to develop scalable systems that inform talent strategy and improve organizational effectiveness.