MaintainX is a mobile-first, IoT- and AI-enabled maintenance and frontline work management platform that digitizes work orders, SOPs, safety inspections, and provides asset health, predictive maintenance, and workforce scheduling.
<h3>About MaintainX</h3> <p>MaintainX is the world's leading mobile-first work execution platform for industrial and frontline teams. We help over <strong>13,000 customers</strong> — including Duracell, McDonald's, Shell, DHL, and Volvo — reduce unplanned downtime and run more efficient operations.</p> <p>In July 2025 we closed a <strong>$150M Series D led by Bessemer Venture Partners</strong>, bringing our total funding to <strong>$254M at a $2.5B valuation</strong>. We were named to the <strong>2025 Forbes Cloud 100</strong> and ranked <strong>#1 in EAM and CMMS</strong> on G2's Summer 2025 report.</p> <p>The market we serve is changing fast: 68% of industrial companies have the same or more downtime than they did in 2024, and there are 3.8M unfilled manufacturing jobs projected through 2033. Our work matters because real plants, real machines, and real frontline workers depend on it.</p> <hr> <h3>The Role</h3> <p>We're hiring a <strong>Senior Product Data Scientist</strong> to join our Product Analytics team. You'll be the first dedicated Data Scientist on a team that has operated as a product analytics function — meaning you'll define what rigorous experimentation and ML-driven insight looks like at MaintainX, and directly influence how our product evolves.</p> <ul> <li>Design and lead product experimentation programs (A/B tests, causal inference) that drive measurable improvements in product adoption and retention</li> <li>Build and deploy ML models — GBMs, random forests, logistic regression — that turn product signals into actionable decisions for PMs and engineering leads</li> <li>Partner cross-functionally with Product, Design, and Engineering to frame business problems as data problems and translate findings into decisions</li> <li>Translate model outputs and experimental results into clear business narratives for senior stakeholders and executives</li> <li>Establish best practices for experimentation and ML workflows</li> </ul> <hr> <h3>You Have</h3> <p><strong>Must-haves:</strong></p> <ul> <li>Senior Product Data Scientist or Senior Data Scientist title with 5–7 years of relevant experience</li> <li>Hands-on experience with product experimentation — A/B testing, causal inference, statistical significance</li> <li>Python proficiency including scikit-learn and MLflow</li> <li>Experience building ML models (GBMs, random forest, linear/logistic regression)</li> <li>Background in B2B SaaS or B2C SaaS</li> <li>Strong cross-functional communication — you've worked directly with PMs, engineers, and designers, not just a sales or finance audience</li> <li>Executive presence: you can turn a complex model output into a business recommendation a VP can act on</li> </ul> <p><strong>Nice-to-haves:</strong></p> <ul> <li>Experience with Databricks</li> <li>Familiarity with Amplitude or similar event analytics platforms</li> </ul> <hr> <h3>We Offer</h3> <ul> <li>Competitive base + equity in a high-growth, post-Series D company</li> <li>Day-1 benefits coverage — health, dental, vision</li> <li>Unlimited PTO</li> <li>$500 home office stipend · $1K annual L&D budget</li> <li>Hybrid hubs in Montreal, Toronto, Raleigh, Miami, and Bay Area</li> </ul> <hr> <h3>How We Work</h3> <p>We reward output. We promote quickly when people deliver, and we have honest conversations early when fit isn't right. If you're energized by ambiguity, care about the people our platform serves, and want to do the most impactful data science work of your career — we'd love to talk.</p> <p></p>