Applied Scientist

$165K - $206K Remote Mid Level Research Scientist

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Skills & Technologies

Python

About This Role

AI job market dashboard showing open roles by category

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 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), 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 Context

This $165K-$206K range is above the median for Research Scientist roles in our dataset (median: $183K across 109 roles with salary data).

Role Details

Company JUUL Labs
Title Applied Scientist
Location Remote, US
Category Research Scientist
Experience Mid Level
Salary $165K - $206K
Remote Yes

About This Role

Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.

The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.

Across the 3,823 AI roles we're tracking, Research Scientist positions make up 3% of the market. At JUUL Labs, this role fits into their broader AI and engineering organization.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

What the Work Looks Like

A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

Skills Required

Python (52% of roles)

PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.

Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.

Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

Compensation Benchmarks

Research Scientist roles pay a median of $223,400 based on 280 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($185K) sits 17% below the category median. Disclosed range: $165K to $206K.

Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.

JUUL Labs AI Hiring

JUUL Labs has 1 open AI role right now. They're hiring across Research Scientist. Based in Remote, US. Compensation range: $206K - $206K.

Remote Work Context

Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% of all AI roles offer remote work.

Career Path

Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.

From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.

The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.

What to Expect in Interviews

Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.

When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

AI Hiring Overview

The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.

The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

The AI Job Market Today

The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 280 roles with disclosed compensation, the median salary for Research Scientist positions is $223,400. Actual compensation varies by seniority, location, and company stage.
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
About 15% of the 3,823 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
JUUL Labs is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from Research Scientist positions include Research Lead, Distinguished Scientist, VP of Research. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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