Business Data Science Manager

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    "datePosted": "2026-04-23T04:00:00.000Z",
    "description": "<h2>Overview</h2>\n<p><strong><u>We built this role and then laughed at ourselves a little. Still meant every word of it</u></strong></p>\n<p>This role asks for hands-on data science chops (Python, ML, real statistical modeling) AND genuine commercial fluency (trade ROI, margin analysis, retailer P&Ls). That combination is genuinely rare, and we're not going to pretend otherwise. If you don't hit every single bullet below, apply anyway. We'd rather talk to someone brilliant with an unconventional path than pass on the right person because their resume doesn't tick every box.</p>\n<p> </p>\n<p><strong><u>What you're walking into</u></strong></p>\n<p>Here's the honest version: you'd be the second dedicated data scientist in our commercial org. The data infrastructure is a work in progress — Microsoft Fabric, D365, and a taxonomy that's still being built. Plan for 6–12 months of plumbing before the elegant modeling takes center stage. If that sounds exciting — building something real from scratch, with real ownership — keep reading. If you need a mature stack on day one, this probably isn't your spot.</p>\n<p> </p>\n<p>What you get in return: genuine autonomy, exposure to the CEO and CFO, models that actually ship, and a director who will geek out on code with you. Oh, and a team with a lot of personality. Forewarned is forearmed.</p>\n<p> </p>\n<p>This is a remote role with an opportunity to work from anywhere in the US. Applicants must be authorized to work for any employer in the U.S. and should not require visa sponsorship now or in the future.</p>\n<p> </p>\n<h2>Responsibilities</h2>\n<p><strong><u>How you'll spend your time</u></strong></p>\n<ul>\n <li>Advanced analytics & model building — ~50%</li>\n <li>Data infrastructure & strategy — ~20%</li>\n <li>Business partnership & storytelling — ~20%</li>\n <li>Omni-channel & e-commerce insights — ~10%</li>\n</ul>\n<p> </p>\n<p><strong><u>The actual job</u></strong></p>\n<p><strong>Build and scale models (the main event).</strong> Time series forecasting, price elasticity, market mix modeling, channel optimization, ML-based attribution. You work in Python. You build from scratch, hand off production-ready outputs, and help scale what's already working.</p>\n<p><strong> </strong></p>\n<p><strong>Do the plumbing.</strong> Cleaning, structuring, and governing data isn't the glamorous part, but it's where the first year goes. You keep stakeholders bought in while the foundation gets built — which takes communication as much as code.</p>\n<p> </p>\n<p><strong>Turn math into decisions.</strong> Regression output into a three-slide exec narrative. You lead with the decision, not the methodology. You can present to a VP who just wants the answer and a data engineer who needs to know what pipeline or metrics the analysis depends on- and you know which conversation you're in.</p>\n<p> </p>\n<p><strong>Coach the team around you.</strong> Two Sales Insights & Analytics Managers handle front-end POS and forecasting. You help them understand what the models mean and how to sell the insights to the business.</p>\n<p> </p>\n<p> </p>\n<h2>Qualifications</h2>\n<p><strong><u>What we're really looking for</u></strong></p>\n<ul>\n <li>A pragmatist, not a show-off. You pick the simplest model that answers the question. You can explain why that was the right call, including what you'd do if the data set was half as clean.</li>\n <li>Real coding ability. Python and SQL. We want the math geek, not the dashboard builder.</li>\n <li>An ethical spine. You tell leadership what the data says — not what they want to hear. Politely, ideally, but you don't roll over.</li>\n <li>Low ego, high collaboration. WD-40 has a strong crew culture. You thrive when you don't always get the credit.</li>\n <li>Curiosity and self-sufficiency. You pick up a new stack in under 90 days and can describe exactly how you did it — not just \"I'm a fast learner.\"</li>\n <li>Resilience under ambiguity. You get a vague question from a VP and come back with the right answer — not just the one that was literally asked.</li>\n <li>Commercial fluency is a plus. CPG, finance, or sales analytics background where you understand margin, trade spend, and how retailers actually think gives you a bit of a head start.</li>\n</ul>\n<p><strong><u>Qualifications</u></strong></p>\n<p><strong>Education:</strong> Bachelor's in a STEM field (math, statistics, computer science, physics, data science, or similar) required. Master's in a STEM field desired.</p>\n<p><strong>Experience:</strong> 5+ years preferred, but if you have 2+ years and you're exceptional, please apply.</p>\n<p><strong>Tech stack:</strong> Python · SQL · Microsoft Fabric / D365 · Power BI or Tableau familiarity helpful.</p>\n<p> </p>\n<h2>About Us</h2>\n<p><strong><u>Why people stay at WD-40</u></strong></p>\n<p>We're not a fast, build-a-big-team environment. What we offer: real ownership of a greenfield function, full remote flexibility, a 70-year-old brand with genuine stability, and a coach who will challenge you technically and trust you to run. If you've been through tech layoffs and want to build something meaningful without the whiplash — that's who we're looking for. Please consider employment with WD-40 Company only if you feel as strongly about our values as we do: We live, breathe, and play by our values <em>every day</em>.</p>\n<p> </p>\n<p><strong><u>Still on the fence? Submit anyway</u></strong></p>\n<p>Research consistently shows that underrepresented candidates — including women — are less likely to apply when they don't hit 100% of a JD. This role describes a genuinely rare combination of skills. If you're deeply strong in some of these areas and honestly curious about the rest, you're closer to our person than you think. We'd love to hear from you.</p>\n<p> </p>\n<p>#LI-CM1</p>\n<p> </p>",
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