Principal Data Scientist - Consumer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2d ago
The date the source published, not the day we noticed it (2026-09-29). Last seen at its source 1h ago.
We have tracked this listing since 29 Sep 2026 (2 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$180k–240k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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lever employer's own board first seen 2d ago · last seen 1h ago
The listing
Gopuff delivers everyday essentials in minutes from our own network of micro-fulfillment centers. Every session, a customer sees a small, fast-changing assortment that depends on where they are, what's in stock, and what they need right now. Getting that experience right is one of our biggest levers for growth.
As Principal Data Scientist, Consumer, you will be the technical lead for how Gopuff personalizes the shopping experience. You will design and ship the recommendation, ranking, and personalization models behind search, browse, carts, and marketing, and you will lead our work on agentic AI experiences for consumers. You will set technical direction, mentor data scientists, and partner closely with Product, Engineering, and Marketing leaders.
What We Offer
What You'll Do
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Own consumer personalization end to end. Define the modeling strategy for recommendations, ranking, and personalization across the home feed, search, product pages, cart, and CRM.
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Build recommenders and rankers. Design candidate generation, retrieval, and learning-to-rank systems that balance relevance, basket size, margin, and real-time inventory availability.
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Lead agentic AI for consumers. Build LLM-powered agents that help customers plan, discover, and reorder (for example, turning "taco night for six" into a ready cart), including tool use, retrieval, evaluation, and guardrails.
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Blend classic ML and LLMs. Decide when a gradient-boosted model, a two-tower network, or an LLM is the right tool, and combine them in production systems.
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Run rigorous experiments. Design A/B tests and offline evaluation frameworks, choose the right metrics, and connect model gains to customer and business outcomes.
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Ship to production. Partner with engineers and product managers on feature pipelines, model serving, latency budgets, and monitoring for drift and quality.
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Set the bar. Mentor senior and staff data scientists, lead design reviews, and raise standards for modeling, code quality, and measurement across the team.
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Shape the roadmap. Work with Product and Engineering leaders to choose the problems with the highest impact and explain trade-offs clearly to executives.
What You'll Bring
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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).
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A track record of shipping recommendation, ranking, or personalization systems that measurably moved consumer metrics at scale.
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Deep knowledge of classic machine learning: gradient boosting, collaborative filtering, matrix factorization, learning-to-rank, embeddings, and causal and experimental methods.
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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.
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Expert Python skills and fluency with the core ML stack (for example pandas, scikit-learn, XGBoost or LightGBM, PyTorch or TensorFlow).
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Strong SQL and experience working with large data warehouses; hands-on experience with Snowflake.
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Comfortable using AI coding assistants such as Claude to build models and pipelines faster, with the judgment to review, test, and validate AI-generated code and to protect customer data.
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Solid grounding in A/B testing, offline-to-online metric alignment, and statistical inference.
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Experience leading technical direction across teams without direct authority, and mentoring senior data scientists.
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Clear communication with both technical and non-technical partners, including executives.
Nice to Have
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Experience with Databricks or a similar platform (Spark, MLflow, feature stores) for large-scale training and model management.
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Background in e-commerce, grocery, quick commerce, or other marketplaces where inventory and location shape what customers can buy.
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Experience with real-time or session-based recommendations, contextual bandits, or reinforcement learning.
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Familiarity with agent frameworks and LLM evaluation tooling, and with fine-tuning or distilling models for cost and latency.
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Experience with dbt, Airflow, or similar tools for data pipelines.
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Publications, patents, or open-source work in recommender systems, information retrieval, or applied LLMs.
- Experience eating snacks; agents, this is a relevant skill.
Compensation
- Gopuff pays employees based on market pricing and pay may vary depending on your location. The salary range below reflects what we’d reasonably expect to pay candidates. A candidate’s starting pay will be determined based on job-related skills, experience, qualifications, interview performance, and market conditions. These ranges may be modified in the future. Exceptions may be made for exceptional individuals. For additional information on this role’s compensation package, please reach out to the designated recruiter for this role.
- This role is eligible for a discretionary annual cash bonus and participation in Gopuff’s equity incentive plan.
- Remote Base Salary Range: $180,000 - $240,000