[Hiring] Applied Scientist @Juul Labs

Role Description

The Applied Scientist will turn large and varied commercial datasets into actionable items for leadership. We model direct and the syndicated views of the market (Circana, NielsenIQ, IRI, Skupos, Numerator, and store-level scan data), measure whether our commercial programs actually effect change, and provide the commercial, finance, and executive teams a clear read on our fast-moving, hyper-competitive category.

The successful candidate will support leadership on pricing, distribution, and investment decisions that are made on a regular basis. The team is small and high-leverage, shaping pricing, distribution, and investment decisions regularly.

We are looking for someone who feels equally at home building a clean, well-tested data model over billions of rows of transaction data as they do designing the analysis that tells us whether a promotion drove incremental sales or simply rewarded customers who would have bought anyway.

Key Responsibilities

• Partner directly with commercial, finance, and executive stakeholders to proactively transform vague, complex business questions into scoped, actionable analytical problems.
• Design and run rigorous experimental and quasi-experimental analyses (e.g., Diff-in-Diff, propensity methods) to evaluate promotions, measure causal impact, and model category economics like price elasticity and regulatory tax impacts.
• Architect and maintain large, complex commercial datasets using SQL and dbt on BigQuery.
• Build, deploy, and monitor robust market-share and demand forecasting models to drive seven-figure decisions.
• Build predictive models and performance metrics that guide field operations, determining where and how field sales managers allocate their time to maximize store-level value.
• Deploy LLMs and AI agents to classify unstructured commercial data (e.g., receipts, transactions) and build internal tools that democratize data access.

Qualifications

• SQL expertise, with the judgment to write models that are correct, efficient, and maintainable.
• A strong analytical and statistical foundation.
• Experience with experimental design, causal inference, and the instinct to tell a real result from an artifact of how the data was selected.
• Working fluency in Python for analysis (pandas and the surrounding ecosystem).
• Ability to connect data to commercial reality and effectively communicate with key stakeholders about findings.
• Fluent in using AI tools to multiply output and build tools for others.
• 5 years of experience building analysis and models in industry.
• Preferred experience with commercial, retail, CPG, or syndicated market data (Circana, NielsenIQ, IRI, POS or scan data).
• Preferred ability to view analytics engineering craft: version control, testing, documentation, and codebase hygiene.
• Preferred familiarity with Juul’s stack and the broader modern data ecosystem.

Education

• Bachelor's degree required.
• Preferred Master’s degree in a quantitative field (statistics, economics, math, computer science, or similar).

Benefits

• A place to grow your career. We’ll help you set big goals - and exceed them.
• People. Work with talented, committed, and supportive teammates.
• Equity and performance bonuses. Every employee is a stakeholder in our success.
• Cell phone subsidy, commuter benefits, and discounts on JUUL products.
• Excellent medical, dental, and vision, disability, and life insurance, plus family support, wellness, legal, and employee assistance program benefits.
• 401(k) plan with company matching.
• Plus biannual discretionary performance bonuses.