About the Team

The People Data Science team empowers the business to unlock the full potential of talent and drive meaningful improvements in organizational effectiveness. By harnessing advanced statistical techniques and machine learning algorithms, we sift through vast amounts of employee data to identify trends, patterns, and correlations that might otherwise remain hidden. Leveraging the insights drawn from these data science methods, we enable our stakeholders to make informed, data-driven decisions, enhance the employee experience, optimize talent density, and foster a work environment that lets our employees thrive.

About the Role

As a Senior Data Scientist on the People Team at DoorDash, you will apply your expertise in graph theory and machine learning to model leadership hierarchies and employee networks, ensuring continuity in people data metrics. You’ll work with large, dynamic datasets to develop graph-based solutions that optimize decision-making and provide actionable insights on leadership transitions, turnover, and organizational structure. This role offers an exciting opportunity to design, implement, and deploy advanced graph analytics models, collaborating with a diverse team of data scientists, engineers, and HR professionals. If you’re passionate about graph theory, network analysis, predictive modeling, and AI-driven workforce intelligence, we’d love to hear from you!

You're excited about this opportunity because you will...

• Pioneer graph-based workforce intelligence: Lead the development of the team’s first graph analytics solutions, shaping how leadership transitions and workforce trends are understood.
• Work with top talent: Collaborate with a highly skilled, cross-functional team of data scientists, engineers, and HR professionals in an innovative, fast-paced environment.
• Leverage cutting-edge technology: Access state-of-the-art cloud tools, graph databases, and large-scale ML models to tackle complex organizational challenges.
• Make a real impact: Use large, dynamic datasets to solve high-stakes business problems and drive data-informed decision-making at scale.
• Grow your career: Benefit from strong support for professional development, continued learning in machine learning, graph analytics, and AI, and mentorship from industry leaders.
• Join a data-driven culture: Be part of a company that values innovation, collaboration, and pushing the boundaries of workforce analytics.

We're excited about you because you have....

• Master’s or Ph.D. in Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, or a closely related field.
• Experience in designing and implementing graph databases (Neo4j, Amazon Neptune, JanusGraph, etc.) and graph query languages (Cypher, Gremlin, SPARQL).
• Strong knowledge of graph theory, network analysis, and predictive modeling.
• Proficiency in Python, SQL, and experience with graph libraries (NetworkX, igraph, TigerGraph).
• Experience with Snowflake, BigQuery, dbt, and building data pipelines.
• Ability to create graph visualizations and dashboards using tools like Tableau, GraphXR, or D3.js.
• Familiarity with AWS, GCP, or Azure for scalable graph-based solutions.
• 3+ years of experience independently applying your skills to solve problems in an industry setting  (1-2+ years in People Analytics preferred)
• Strong understanding of ML libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Significant experience with production-level ML systems and end-to-end machine learning pipelines
• Nice-to-have: 
• Experience working in a global HR / people organization. 
• Understanding of workforce metrics, turnover analysis, and HRIS systems like Workday.

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

Compensation

The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related facto