Job description

MaintainX is a leading mobile-first work execution platform for industrial and frontline teams. More than 13,000 customers, including Duracell, McDonald's, Shell, DHL and Volvo, use MaintainX to cut unplanned downtime and run better operations, across 13.9 million managed assets and 79.5 million completed work orders. In August 2026 MaintainX became part of Autodesk, joining Autodesk Operations Solutions adsknews.autodesk.com, the organization unifying Autodesk's operations platform alongside Tandem, FlexSim and Fusion Operations. Autodesk's strategy is to converge design, make and operate into one continuous lifecycle: design an asset, build it, run it, then feed what you learn running it back into the next design. Autodesk had design and make. Operate is the phase that tells you what actually happened, and it is ours. 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 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 Our mission is to keep the physical world running. Factories, fleets, hospitals and campuses stay up because the people who maintain them have tools worth using. That is what we build. Compensation and benefits. Base pay is one part of the package. Depending on the role, compensation may also include commission, an annual bonus and equity. Benefits differ by country. For roles in the United States, Autodesk’s benefits are described at benefits.autodesk.com benefits.autodesk.com. For roles in Canada and other countries, the plan differs on health coverage, retirement and leave, and your recruiter will walk you through it. Belonging. We take pride in a culture where everyone can thrive. More at autodesk.com/company/global-belonging autodesk.com. More on where this is going: Autodesk CEO Andrew Anagnost on building the future of connected operations, and AOS SVP Stephen Hooper on welcoming MaintainX to Autodesk.

Requirements

Must-haves

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
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
Our mission is to keep the physical world running. Factories, fleets, hospitals and campuses stay up because the people who maintain them have tools worth using. That is what we build.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlpython

Platform: ashby
Effort: quick