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Senior Data Scientist

Juul Labs -
Remote

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Job Details

$165,000 - $206,000 a year

Benefits

Commuter assistance
Disability insurance
Health insurance
Dental insurance
Employee assistance program
Vision insurance
401(k) matching
Life insurance

Qualifications

Bachelor's degree
Data-driven problem-solving

Full Job Description

THE COMPANY:

Juul Labs's mission is to transition the world's billion adult smokers away from combustible cigarettes, eliminate their use, and combat underage usage of our products. We have the opportunity to address one of the world's most intractable challenges through a commitment to exceptional quality, research, design, and innovation. Backed by leading technology investors, we are committed to the same excellence when it comes to hiring great talent.

We are a diverse team that is united by this common purpose and we are hiring the world's best engineers, scientists, designers, product managers, operations experts, and customer service and business professionals. If the opportunity to build your career is compelling, read on for more details.

ROLE AND RESPONSIBILITIES:

The Data 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), we measure whether our commercial programs actually effect change, and we give the commercial, finance, and executive teams a clear read on our fast-moving, hyper-competitive category. The Applied Scientist team is a small group but creates impactful changes at Juul. The successful candidate will have the ability to support leadership on pricing, distribution, and investment decisions that are made on a regular basis. The team is small and high-leverage, and our work shapes pricing, distribution, and investment decisions on a regular basis.

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. We believe the best data people do both, and we have built the team around that conviction.

KEY RESPONSIBILITIES:

Partner directly with commercial, finance, and executive stakeholders to proactively transform vague, complex business questions into scoped, actionable analytical problems, anticipating organizational needs before they are explicitly asked
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, and build, deploy, and monitor robust market-share and demand forecasting models to drive seven-figure decisions
Build the predictive models and performance metrics that guide field operations, directly 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 and enable stakeholders to answer their own questions.

PERSONAL AND PROFESSIONAL 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 your findings.
Fluent in using AI tools to multiply your own output and to 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)

JUUL LABS PERKS & 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

Juul Labs is proud to be an equal opportunity employer and is committed to creating a diverse and inclusive work environment for all employees and job applicants, without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. We will consider for employment qualified applicants with arrest and conviction records, pursuant to the San Francisco Fair Chance Ordinance. Juul Labs also complies with the employment eligibility verification requirements of the Immigration and Nationality Act. All applicants must have authorization to work for Juul Labs in the US. #LI-remote

Apply Now

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