Principal Data Scientist

JWC Distribution Inc.; United States; On-site; USD 200,000 - 250,000; Full time

Job summary

An innovative ecommerce firm is seeking a Principal Data Scientist to join their remote team in the United States. In this leadership role, you will define the vision for data strategy and drive impactful decisions through analytics and forecasting. Candidates must have robust analytics skills, experience with Python and SQL, and the ability to thrive in a startup environment. This position offers a competitive salary ranging from $200,000 to $250,000 annually.

Qualifications

• Senior-level operator who can own outcomes end-to-end.
• Strong communication skills to explain data-driven insights.
• Ability to thrive in ambiguity and fast-paced environments.

Responsibilities

• Identify opportunities and drive outcomes from data analysis.
• Build systems that improve forecasting and purchasing decisions.
• Work closely with engineering to create scalable data models.

Skills

Strong analytics + statistics fundamentals

Ability to design and ship data models + dashboards

Strong communication

High ownership

Comfort operating in a lean environment

Tools

Python

SQL

Job description

Please apply to learn more. The company is intentionally private and difficult to research ahead of time. Happy to share why on our first call.

Are you obsessed with data, taking action, and building systems that create real business outcomes? If you have a whole lot of hustle and a touch of nerd and you want true ownership instead of "just another dashboard request" come work with JWC Distribution Inc.

JWC Distribution Inc. is one of the largest Amazon sellers in the sportswear and outdoors niche. We operate fully remote with a mix of U.S. based leadership and an overseas operations team. We move fast, we prioritize impact, and we're building a data-driven engine to improve purchasing, forecasting, inventory decisions, and profitability.

We're hiring a Principal Data Scientist who thinks like an intrapreneur: someone who can see the end goal, design the solution, and drive it to completion—partnering closely with engineering and operations along the way.

Company Description

JWC Distribution Inc. is a remote-first ecommerce business operating at scale on Amazon in the sportswear/outdoors category. We're a lean team of 8 full-time employees and expanding quickly. We combine a small senior team with strong operational support to execute quickly and consistently. The work is hands-on, the feedback loop is short, and the best ideas win.

This is a startup environment. If you thrive in ambiguity, want to build something from the ground up, and are energized (not intimidated) by wearing multiple hats—keep reading. If you prefer large teams, established processes, and narrowly scoped responsibilities, this isn't the right fit.

The Role

Type: Full-time, Remote

Salary range (USD): $200,000 - $250,000 per year

Important: We are unable to provide H-1B visa sponsorship for this position. Candidates must be authorized to work in the United States without sponsorship.

This is not a "research" role and not a "reporting-only" role. This is a build-the-machine role where the machine is the analytics + forecasting + data feedback loops that drive better business decisions.

You will own the data division. This is a leadership role where you'll define the vision, build the systems, and shape how data drives decisions across the entire company. If you've been waiting for the opportunity to lead rather than execute someone else's roadmap, this is it.

You will work closely with our senior engineer to create consistent data feedback loops and scalable analytical systems. You will also have access to a team that can support execution when legwork is needed (validation, structured inputs, operational QA, etc.). The expectation is that you can take ambiguous problems and turn them into shippable, measurable outcomes.

What is a day in the life of a Data Scientist at JWC?

• Partner with the owner and senior engineer to identify the highest-leverage opportunities (forecasting, purchasing, inventory, pricing, margin, in-stock, operations)
• Translate "messy" business questions into crisp analytical deliverables and measurable outcomes
• Build and refine models and decision systems (forecasting, replenishment logic, anomaly detection, margin/price guardrails, KPI definitions)
• Create scalable, operator-friendly data visualizations that drive action—not just visibility
• Design data models and pipelines (SQL and/or Python) that produce reliable, repeatable outputs
• Implement quality checks so teams trust the data and actually use it
• Present findings and recommendations clearly, and follow through to implementation
• Build systems that reduce manual work and create leverage across the business

What will I need to thrive in this role?

We're looking for a senior-level operator who can own outcomes end-to-end.

Must-haves

• Strong analytics + statistics fundamentals (and practical judgment, not just theory)
• Ability to design and ship data models + dashboards that are used in real operations
• Strong communication: you can explain what matters, what doesn't, and why
• High ownership: you don't need a detailed spec to start creating value
• Comfort operating in a lean, fast-moving environment with imperfect data
• Authorized to work in the United States without visa sponsorship

Nice-to-haves (not required)

• Forecasting / inventory planning experience (seasonality, lead times, stock targets)
• Python (or R) for analysis, automation, and modeling
• Experience building decision systems (not just insights)

What does high performance look like?

• You consistently deliver decision-grade insights and systems that increase profitability or reduce risk
• Forecasting and purchasing decisions improve measurably over time
• Manual processes get automated; operations become more scalable
• Dashboards don't just exist—they drive actions and accountability
• You identify opportunities proactively and take full ownership to completion
• You balance speed with correctness (you know when "good enough" is good enough, and when precision matters)

What is my potential for career growth?

This role touches nearly everything: BI visualization, analytics, forecasting, process engineering, data engineering, and operational decision-making. As the leader of our data function from day one, you'll have the opportunity to scale the team and capability as the company grows. Whether that means hiring your own team, expanding automation, or building a larger decision intelligence platform—you'll shape what comes next.

What does success look like in the first 30, 60, 90 days?

30 Days:

• Understand our current data, workflows, KPIs, and decision points
• Identify quick wins (data quality, metric definitions, dashboard improvements, automation opportunities)
• Build trust by delivering useful outputs fast

60 Days:

• Ship net-new dashboards/models tied directly to purchasing, inventory, or margin outcomes
• Establish a reliable workflow with engineering + operations (request → build → validate → deploy → iterate)
• Improve data consistency and reduce "multiple versions of the truth"

90 Days:

• Own an end-to-end system (v1) that meaningfully impacts forecasting/replenishment/purchasing decisions
• Be able to independently take a request/idea from inception through delivery, validation, and adoption
• Deliver measurable improvements (efficiency, accuracy, margin, in-stock, or risk reduction)

What is the team like?

You’ll work directly with the owner and collaborate closely with a senior engineer. You’ll also have operational support from an overseas team for execution-heavy work when needed. With only 8 full-time employees, you’ll have a seat at the table and direct impact on company direction. We’re small, fast, and impact-driven. The goal is to ship systems that make the business better—quickly and consistently.

Sounds great. What's the company culture?

• Owner Mindset: You treat the business like it’s yours: you care about outcomes, you follow through, and you take responsibility.
• Data Fanatics: You don't guess. You validate. You measure. You keep score. You change your mind when the data proves you wrong.
• Bias to Action: We move quickly, test, and iterate. Momentum matters—without sacrificing correctness where it counts.
• Builders (Not Ticket Takers): We build systems that scale and reduce recurring pain. We don't just "answer questions"—we make questions easier to answer forever.

What is the hiring process?

• Technical interview (SQL + analytics reasoning; practical scenarios)
• Working session (how you'd approach a real JWC problem)
• References
• Offer

How can I stand out as an applicant?

• Quantify impact: margin gains, forecast improvements, automation saved hours, improved accuracy, reduced stockouts, etc.
• Share artifacts: dashboards, repos, writeups, models—anything tangible
• Explain how you validate data quality and avoid building on bad assumptions
• Show that you can own outcomes end-to-end (not just produce analysis)