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Juul Labs

Data Scientist

Posted 19 Days Ago
Remote
Hiring Remotely in United States
165K-206K Annually
Senior level
Remote
Hiring Remotely in United States
165K-206K Annually
Senior level
Build and maintain large commercial datasets and predictive/forecasting models (BigQuery, dbt, SQL, Python). Design causal and experimental analyses to measure promotion impact and price elasticity. Partner with commercial, finance, and executive stakeholders to inform pricing, distribution, and investment. Deploy LLMs and AI agents to classify unstructured data and build tools that democratize data access.
The summary above was generated by AI

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

SALARY RANGES:
Salary varies by role, level and location, and is dependent on the cost of labor in a given
geographic region among other factors. These ranges may be modified at any time.
LOCATIONS:
Tier 1 Locations: Greater New York City, and San Francisco Bay Area
Tier 2 Locations: Greater Boston, Washington DC Metropolitan Area, Seattle/Tacoma,
Greater Sacramento, Southern California (Los Angeles/OC/San Diego, Riverside and Imperial counties)
Tier 3 Locations: Rest of New England, NY Capital District, Rest of New Jersey, Greater
Philadelphia, Pittsburgh, Delaware, Rest of Maryland, Rest of Virginia, North Carolina,
Atlanta, Miami-Fort Lauderdale-WPB, Chicagoland, Dallas, Houston, Austin,
Minneapolis/St. Paul, Colorado, Phoenix, Las Vegas, Reno, Carson City NV., Portland Ore./Vancouver
Wash., Rest of California, Hawaii
Tier 4 Locations: Rest of US including Alaska and Puerto Rico

Tier 1 Range:
$165,000$206,000 USD
Tier 2 Range:
$150,000$187,000 USD
Tier 3 Range:
$141,000$176,000 USD
Tier 4 Range:
$126,000$157,000 USD

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