Principal Data Scientist – Consumer

Gopuff

. Serve as the technical lead for Gopuff’s consumer personalization strategy .

Posted 9/29/2026full-timeRemote • United StatesLead💰 $180,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing recommendation and personalization systems using classic machine learning and LLMs, with a strong focus on A/B testing and statistical evaluation. Proven ability to lead technical direction, mentor data scientists, and communicate effectively with both technical and non-technical stakeholders.

Highest-signal resume keywords

10+ Years Experience In Data ScienceExpert Python SkillsDeep Knowledge Of Classic Machine LearningHands-On Experience With LLMsStrong SQL Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Recommendation SystemsMachine LearningA/B TestingStatistical InferenceGradient BoostingCollaborative FilteringMatrix FactorizationLearning-To-RankEmbeddingsCausal Methods

Soft Skills

Clear CommunicationMentoring

Tools & Technologies

PandasScikit-LearnXGBoostLightGBMPyTorchTensorFlowSnowflakeDatabricksAirflowClaude

Industry Keywords

E-CommerceQuick-CommerceMarketplace ExperienceReal-Time RecommendationsContextual BanditsReinforcement LearningAgent FrameworksLLM Evaluation Tooling

Tech Stack

Tools & technologies

AirflowPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Serve as the technical lead for Gopuff’s consumer personalization strategy
Define modeling strategy for recommendations, ranking, and personalization across the home feed, search, product pages, cart, and CRM
Design candidate generation, retrieval, and learning-to-rank systems balancing relevance, basket size, margin, and real-time inventory
Build LLM-powered agentic AI experiences that help customers plan, discover, and reorder
Combine classic machine learning and LLMs in production systems
Design A/B tests and offline evaluation frameworks, select metrics, and connect model gains to customer and business outcomes
Partner with engineering and product managers on feature pipelines, model serving, latency budgets, and monitoring
Mentor senior and staff data scientists, lead design reviews, and raise standards for modeling, code quality, and measurement
Work with Product and Engineering leaders to prioritize high-impact problems and explain trade-offs to executives

Requirements

What you’ll need

10+ years of experience in data science or machine learning, or 8+ years with a PhD in a quantitative field (computer science, statistics, operations research, or similar)
Track record of shipping recommendation, ranking, or personalization systems that measurably moved consumer metrics at scale
Deep knowledge of classic machine learning: gradient boosting, collaborative filtering, matrix factorization, learning-to-rank, embeddings, and causal and experimental methods
Hands-on experience building agentic AI systems with LLMs, including prompt and tool design, retrieval-augmented generation, multi-step agents, and evaluation of agent quality and safety
Expert Python skills and fluency with pandas, scikit-learn, XGBoost or LightGBM, PyTorch or TensorFlow
Strong SQL and experience working with large data warehouses; hands-on experience with Snowflake
Comfort using AI coding assistants such as Claude, with the judgment to review, test, and validate AI-generated code and protect customer data
Solid grounding in A/B testing, offline-to-online metric alignment, and statistical inference
Experience leading technical direction across teams without direct authority and mentoring senior data scientists
Clear communication with technical and non-technical partners, including executives
Nice to have: Databricks or similar platforms, e-commerce/grocery/quick-commerce or marketplace experience, real-time or session-based recommendations, contextual bandits or reinforcement learning, agent frameworks and LLM evaluation tooling, model fine-tuning or distillation, dbt, Airflow, publications, patents, or open-source work

Benefits

Comp & perks

Medical/Dental/Vision Insurance
401(k) Retirement Savings Plan
HSA or FSA eligibility
Long and Short-Term Disability Insurance
Fitness Reimbursement Program
25% employee discount & FAM Membership
Flexible PTO
Group Life Insurance
EAP through AllOne Health (formerly Carebridge)
Discretionary annual cash bonus
Participation in Gopuff’s equity incentive plan