Applied Scientist at Juul Labs

The Company

Juul Labs' mission is to transition adult smokers away from combustible cigarettes, eliminate their use, and combat underage usage of our products. We are committed to addressing one of the world's most intractable challenges through exceptional quality, research, design, and innovation. Backed by leading technology investors, we apply the same excellence to hiring top talent. We are a diverse team united by this common purpose and are seeking the world's best engineers, scientists, designers, product managers, operations experts, and business professionals.

Role and Responsibilities

The Applied Scientist will transform large and varied commercial datasets into actionable items for leadership. This involves modeling direct and syndicated market views (Circana, NielsenIQ, IRI, Skupos, Numerator, and store-level scan data), measuring the impact of commercial programs, and providing clear insights to commercial, finance, and executive teams in a fast-moving, hyper-competitive category. The Applied Scientist team is small but drives impactful changes at Juul. The successful candidate will support leadership on pricing, distribution, and investment decisions made regularly. This high-leverage role's work directly shapes these critical business decisions.

We are looking for someone who is equally adept at building clean, well-tested data models over billions of rows of transaction data and designing analyses to determine if a promotion drove incremental sales or simply rewarded existing customers. We believe the best data professionals excel at both, and our team is built around this conviction.

Key Responsibilities

• Strategic Problem Solving: Partner directly with commercial, finance, and executive stakeholders to transform vague, complex business questions into scoped, actionable analytical problems, anticipating organizational needs before they are explicitly asked.
• Causal Inference & Experimentation: Design and execute 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.
• Data Architecture & Modeling: 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 guide seven-figure decisions.
• Predictive Analytics for Field Operations: Build predictive models and performance metrics that guide field operations, directly determining how field sales managers allocate their time to maximize store-level value.
• AI & ML Deployment: Deploy LLMs and AI agents to classify unstructured commercial data (e.g., receipts, transactions) and build internal tools that democratize data access and empower stakeholders to answer their own questions.

Personal and Professional Qualifications

• SQL Expertise: Strong SQL skills, with the judgment to write correct, efficient, and maintainable data models.
• Analytical Foundation: A robust analytical and statistical foundation.
• Causal Inference: Experience with experimental design, causal inference, and the ability to distinguish real results from data artifacts.
• Python Proficiency: Working fluency in Python for analysis (pandas and the surrounding ecosystem).
• Business Acumen: Ability to connect data to commercial reality and effectively communicate findings to key stakeholders.
• AI Fluency: Proficient in using AI tools to enhance personal output and build tools for others.
• Industry Experience: 5 years of experience building analyses and models in an industry setting.
• Preferred Experience: Commercial, retail, CPG, or syndicated market data (Circana, NielsenIQ, IRI, POS or scan data).
• Preferred Analytics Engineering: Ability to apply analytics engineering craft, including version control, testing, documentation, and codebase hygiene.
• Preferred Tech Stack Familiarity: Familiarity with Juul’s technology stack and the broader modern data ecosystem.

Education

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

Juul Labs Perks & Benefits

• Career Growth: Opportunities to set and exceed ambitious career goals.
• Team Environment: Work with talented, committed, and supportive teammates.
• Financial Incentives: Equity and performance bonuses, making every employee a stakeholder.
• Perks: Cell phone subsidy, commuter benefits, and discounts on JUUL products.
• Comprehensive Benefits: Excellent medical, dental, and vision insurance, disability and life insurance, family support, wellness programs, legal services, and an employee assistance program.
• Retirement: 401(k) plan with company matching.
• Bonuses: Biannual discretionary performance bonuses.

Equal Opportunity Employer

Juul Labs is proud to be an equal opportunity employer committed to creating a diverse and inclusive work environment. We do not discriminate based on race, color, religion, sex, sexual orientation, age, gender identity or expression, national origin, disability, or veteran status. We comply with all applicable employment laws, including those related to background checks. All applicants must have authorization to work for Juul Labs in the US. #LI-remote

Salary Ranges

Salary varies by role, level, and location, influenced by factors such as cost of labor in a geographic region. These ranges may be updated. The following ranges are provided for reference:

• Tier 1 Locations (Greater NYC, SF Bay Area): $165,000—$206,000 USD
• Tier 2 Locations (Greater Boston, DC Metro, Seattle/Tacoma, SoCal, etc.): $150,000—$187,000 USD
• Tier 3 Locations (Rest of NE, NY Capital Dist., Rest of NJ, etc.): $141,000—$176,000 USD
• Tier 4 Locations (Rest of US, AK, PR): $126,000—$157,000 USD