Senior Product Data Scientist

MaintainX; San Francisco (CA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Flexible time off

Competitive salary and equity

Training and development investments

Comprehensive healthcare coverage

Job summary

MaintainX is seeking a Senior Product Data Scientist to join the Product Analytics team in San Francisco. You will be the first dedicated data scientist, defining rigorous experimentation and ML-driven insights to shape our product.

You will design product experiments, build ML models (GBMs, RF, LR), and translate results into decisions for PMs and engineers, collaborating with Product, Design, and Engineering to drive adoption and retention.

Qualifications

• 5–7 years of experience in data science or ML roles.
• Proficient in Python and ML tooling.
• Experience in B2B/B2C SaaS environments.
• Experience with product experimentation and A/B testing.

Responsibilities

• Design and lead product experimentation programs including A/B tests.
• Build and deploy ML models to inform PMs and engineers.
• Translate model outputs into business recommendations for stakeholders.
• Establish best practices for ML workflows.

Skills

Python

A/B testing

Causal inference

Cross-functional communication

Executive presence

5-7 years exp

Product analytics

Education

Bachelor's degree (related field)

Tools

Databricks

Amplitude

scikit-learn

MLflow

Job description

• 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

Benefits

• Flexible time off


• Competitive salary and equity opportunities


• Training and development investments


• Comprehensive healthcare coverage

Python proficiency including scikit-learn and MLflowHands-on experience with product experimentation — A/B testing, causal inference, statistical significanceBackground in B2B SaaS or B2C SaaSStrong cross-functional communication — you’ve worked directly with PMs, engineers, and designers, not just a sales or finance audienceExecutive presence: you can turn a complex model output into a business recommendation a VP can act onSenior Product Data Scientist or Senior Data Scientist title with 5–7 years of relevant experienceExperience building ML models (GBMs, random forest, linear/logistic regression)Experience with DatabricksFamiliarity with Amplitude or similar event analytics platforms