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About This Role
Who We Are
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At Justworks, you’ll enjoy a welcoming and casual environment, great benefits, wellness program offerings, company retreats, and the ability to interact with and learn from leaders in the startup community. We work hard and care about our most prized asset \- our people.
We’re helping businesses get off the ground by enabling them to focus on running their business. We solve HR issues. We’re data\-driven and never stop iterating. If you’d like to work in a supportive, entrepreneurial environment, are interested in building something meaningful and having fun while doing it, we’d love to hear from you.
We're united by shared goals and shared motivations at Justworks. These are best summed up in our company values, which are reflected in our product and in our team.
If this sounds like you, you’ll fit right in.
Department
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Technology, Data \& Analytics Team
Who You Are
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You're an experienced data scientist who gets excited about understanding how customers interact with a product – and using that understanding to help teams make smarter decisions. You're a trusted data storyteller: you can write a tight SQL query, design a rigorous experiment, and then turn those findings into a narrative that moves a roadmap. You believe that the best data science work accelerates learning, improves decision making, and ultimately drives measurable impact for customers and the business.
Justworks is looking for a Senior Data Scientist to join our Product Analytics group within the Data \& Analytics team. You'll partner across Product, Engineering, Design, Finance, Marketing, and Revenue to define success metrics, run experiments, size opportunities, and build a data\-informed approach to how we grow and improve our product.
Your Success Profile
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What You Will Work On
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Lead end\-to\-end analytics projects, from defining metrics to analyzing data and delivering insights
- Partner with product leaders to define and measure goal metrics
- Design and analyze A/B tests, quasi\-experiments, and causal analyses to measure the impact of product changes and help teams understand not just *if* something worked, but *why*
- Accelerate product learning cycles through frameworks for experimentation, measurement, and iteration so teams can move faster without sacrificing rigor
- Analyze strategic opportunities to inform roadmap prioritization
- Build compelling narratives from complex data, presenting findings in ways that influence decisions with both technical and non\-technical audiences, from product pods to senior leadership
- Identify friction and opportunity across the customer lifecycle, from onboarding flows to feature adoption to retention signals, and translate what you find into actionable strategies
- Develop and apply AI\-assisted approaches to analysis, insight delivery, and data workflows to multiply your impact and expand the reach of data science across the organization
- Partner with data engineering and analytics engineering to improve data foundations, instrument key events, and ensure the right data exists to answer the questions product teams are asking
- Perform other related responsibilities as needed based on department and/or organizational needs.
How You Will Do Your Work
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In the Data Scientist role, *how* results are achieved is paramount for your success and ultimately result in our success as an organization. In this role, your foundational knowledge, skills, abilities and personal attributes are anchored in the following competencies:
Good judgment \- the exercise of critical thinking, analyzing and assessing problems and implications, identifying patterns, making connections of underlying issues, understanding risks and developing mitigation strategies, and taking ownership of the outcome.Teamwork and communication \- putting our collective best together through documentation, collaboration, relationship\-building, listening, empathy, recruiting, and evangelism.Influence and leadership \- fostering a community of knowledge\-sharing, collaboration, mentorship, and forward\-thinking. This includes helping product partners develop a more data\-informed mindset, not just answering their questions.Skills and knowledge \- the capacity to actively learn and apply specific domain knowledge, know\-how, and best practices to continually enhance and improve.
In addition, all Justworkers focus on aligning their behaviors to our core values known as COGIS. It stands for:
- Camaraderie \- Day to day you can be seen working together toward a higher purpose. You like to have fun. You’re an active listener, treat people respectfully, and have a strong desire to know and help others.
- Openness \- Your default is to be open. You're willing to share information, understand other perspectives, and consider new possibilities. You’re curious, ask open questions, and are receptive to thoughts and feedback from others.
- Grit \- You demonstrate grit by having the courage to commit and persevere. You’re committed, earnest, and dive in to get the job done well with a positive attitude.
- Integrity \- Simply put, do what you say and say what you'll do. You’re honest and forthright, have a strong moral compass, and strive to match your words with your actions while leading by example.
- Simplicity \- Be like Einstein: “Everything should be made as simple as possible, but no simpler.”
Qualifications
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- 7\+ years of experience as a data scientist or analyst, with a track record of driving business impact through statistical analysis, experimentation, and predictive modeling
- Strong expertise in experimental design, causal inference, and statistical methods — you know how to draw defensible conclusions from imperfect data
- Excellent communication and data storytelling skills — you can translate complex findings into clear narratives that influence strategy and decisions at all levels of the organization
- Strong business acumen and the ability to connect analysis to product strategy, roadmap tradeoffs, and business outcomes
- Proficient in at least one statistical programming language (Python or R)
- Fluent in SQL
- Familiarity with a cloud\-based data stack (e.g. Snowflake, dbt)
- Demonstrated curiosity about AI tools and emerging technologies, with a track record of applying them to accelerate analysis, improve rigor, or expand the reach of data science work
- Prior experience in a high\-growth startup or SaaS company is preferred
The base wage range for this position based in our New York City Office is targeted at $167,500\.00 \- $184,250\.00 per year.
\#LI\-DG2 \#LI\-Hybrid
Actual compensation is based on multiple factors that are unique to each candidate, including and not limited to skill set, level of relevant experience, and specific work location. Salary ranges for positions based in other locations may differ based on the cost of labor in that location.
Diversity At Justworks
==========================
Justworks is committed to maintaining a workplace where diversity of identity, culture, and life experience is the norm and is celebrated authentically and respected consistently. Diversity in our work, our people, and our product drives creativity and innovation, entrepreneurial leadership and integrity, competitiveness, and collaboration throughout our business and in the market. We depend on our differences to make our team stronger, our workplace more dynamic, and our product accessible to all of our customers.
We’re proud to be an equal opportunity employer open to all qualified applicants regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital or familial status, disability, pregnancy, gender identity or expression, veteran status, genetic information, or any other legally protected status. Justworks is fully dedicated to providing necessary support to candidates with disabilities who may require reasonable accommodations. We also provide reasonable accommodations to employees based on their sincerely held religious beliefs, as well as for other covered reasons consistent with applicable federal, state, and local laws. If you're in need of a reasonable accommodation, please reach out to us at [email protected]. Your comfort and success matter to us, and we're here to ensure an inclusive experience.
Salary Context
This $167K-$184K range is above the median for Data Scientist roles in our dataset (median: $169K across 153 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 2,799 AI roles we're tracking, Data Scientist positions make up 7% of the market. At Justworks, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $200,350 based on 604 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,500. This role's midpoint ($175K) sits 12% below the category median. Disclosed range: $167K to $184K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,760; Mid: $159,385; Senior: $227,500; Director: $242,000; VP: $250,000.
Justworks AI Hiring
Justworks has 2 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer. Based in New York, NY, US. Compensation range: $152K - $184K.
Location Context
AI roles in New York pay a median of $208,300 across 2,241 tracked positions. That's 4% above the national median.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 2,799 open positions tracked in our dataset. By seniority: 98 entry-level, 1,283 mid-level, 1,092 senior, and 326 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (460 positions). The remaining 2,318 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 30 roles); AI Safety ($274,200 median, 43 roles); Research Engineer ($260,000 median, 387 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 2,799 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (1,978), AI Software Engineer (197), Data Scientist (195). 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 (98) are outnumbered by mid-level (1,283) and senior (1,092) 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 326 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (460 positions), with 2,318 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 $200,000. Top-quartile roles start at $252,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,433 postings), Aws (840 postings), Rag (663 postings), Azure (639 postings), Gcp (537 postings), Pytorch (445 postings), Prompt Engineering (418 postings), Claude (396 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
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