About the role
MaintainX is the world's leading AI-powered maintenance and asset management platform, serving 13,000+ customers including Duracell, Shell, Cintas, and Brenntag. We raised $150M in Series D funding led by Bessemer Venture Partners and Bain Capital Ventures, bringing our total funding to $254M. We were named to the Forbes 2025 Cloud 100 , the definitive ranking of the top 100 private cloud companies in the world. We're growing fast and hiring the talent to match. About MaintainX MaintainX is the world's leading mobile-first work execution platform for industrial and frontline teams. We help over 13,000 customers — including Duracell, McDonald's, Shell, DHL, and Volvo — reduce unplanned downtime and run more efficient operations. In July 2025 we closed a $150M Series D led by Bessemer Venture Partners , bringing our total funding to $254M at a $2.5B valuation . We were named to the 2025 Forbes Cloud 100 and ranked #1 in EAM and CMMS on G2's Summer 2025 report. 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.
The Role We're hiring a Senior Product Data Scientist 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. Design and lead product experimentation programs (A/B tests, causal inference) that drive measurable improvements in product adoption and retention Build and deploy ML models — GBMs, random forests, logistic regression — that turn product signals into actionable decisions for PMs and engineering leads Partner cross-functionally with Product, Design, and Engineering to frame business problems as data problems and translate findings into decisions Translate model outputs and experimental results into clear business narratives for senior stakeholders and executives Establish best practices for experimentation and ML workflows You Have Must-haves: Senior Product Data Scientist or Senior Data Scientist title with 5–7 years of relevant experience Hands-on experience with product experimentation — A/B testing, causal inference, statistical significance Python proficiency including scikit-learn and MLflow Experience building ML models (GBMs, random forest, linear/logistic regression) Background in B2B SaaS or B2C SaaS Strong cross-functional communication — you've worked directly with PMs, engineers, and designers, not just a sales or finance audience Executive presence: you can turn a complex model output into a business recommendation a VP can act on Nice-to-haves: Experience with Databricks Familiarity with Amplitude or similar event analytics platforms We Offer Competitive base + equity in a high-growth, post-Series D company Day-1
