Lead Data Scientist

Description

The company makes a mobile family safety app, tracking devices for items, and a GPS tracker for pets. Its services include location sharing, safe driver reports, and crash detection with emergency dispatch. It had about 102.4 million monthly active users as of June 30, 2026, across more than 180 countries.

The company has over 500 employees, and it is remote first, so most people work remotely. It describes itself as AI native, meaning AI is built into how the team builds and runs the product.

The Revenue Experimentation team sits in the Direct Revenue group. It runs fast experiments on ads, subscriptions, and one-time purchases, including pricing, paywalls, ad placement and mediation, and upgrade flows. Its findings shape revenue for nearly 100 million members. The team treats AI as a working partner in ideation, coding, testing, review, and iteration.

This Lead Data Scientist role owns the full path from a revenue opportunity to machine learning in production for Direct Revenue, which grows active users, subscriptions, paid transactions, and in-app advertising. You will find opportunities, estimate their size, agree priorities with business leads, and ship models with the team's data scientists and engineers.

The team is expanding into consumer-facing ads, including recommendations and personalization, and needs a senior scientist who understands the problem deeply and can get models live. In your first year, you will help increase how much production ML the team delivers and help set the roadmap with the data science lead and the product manager.

Responsibilities

• Investigate revenue options and the data behind them, then use that work to size, scope, and measure product changes in Databricks.
• Design, build, deploy, and run production ML systems, including batch inference, online services, and online learning models, on the team's feature store and model registry for personalization, experimentation, and automation.
• Work with Product, Mobile Engineering, Cloud Engineering, Data Engineering, and MLOps to bring these systems into user-facing features.
• Set up monitoring for new ML features so you can track their performance and business impact.
• Track lineage for data, code, and model artifacts so the ML lifecycle stays compliant, reproducible, and secure.
• Improve the data ecosystem alongside Data Engineering, including the pipelines that feed experiments and ML.
• Mentor other data scientists and set best practices for advanced analytics and ML system development.
• Use Claude Code and other AI tools for data discovery, modeling, and experiment evaluation.

Requirements

• An advanced degree in a field that depends on rigorous statistical analysis, or equivalent industry experience.
• 6+ years scoping, building, and analyzing ML-powered systems, including models you have shipped to production.
• Significant hands-on work in Python, scikit-learn, PySpark, and causal inference programming languages, with good software engineering habits such as testing, modular code, and version control.
• Formal training and professional experience with modern causal inference and causal analysis methods.
• Significant experience working with found data, guiding instrumentation to collect new data, and building transformations for complex analyses and ML systems.
• Hands-on experience designing, monitoring, and analyzing experiments in consumer technology.
• Experience building ML or running experiments at a business-to-consumer technology company, ideally on revenue work such as subscriptions, transactions, or ads.
• Strong communication and project leadership skills, with the ability to influence cross-functional teams.
• Ability to work through ambiguous problems in a structured, hypothesis-driven way backed by data.
• Prior experience using LLMs in advanced data processing and analysis workflows.
• Preferred: experience with modern digital advertising and ad tech infrastructure.
• Preferred: experience with ranking and grouping algorithms for content feeds.
• Preferred: experience contributing to or managing production feature stores and ML model registries.
• Preferred: experience working with product line general managers, including revenue reporting and forecasting.
• Preferred: experience with subscription products, lifecycle marketing, or user acquisition.
• Preferred: experience with geospatial data and mobile location-based services.
• AI-native expectations: run several workstreams in parallel instead of guiding one agent at a time.
• AI-native expectations: review AI-generated code, analyses, and models as carefully as a colleague's pull request, and take ownership of everything you ship.
• AI-native expectations: deliver more production ML, faster, by using AI well.
• AI-native expectations: share your AI workflows and help the data scientists and engineers around you raise their AI skills.
• AI-native expectations: keep up with new AI tools and techniques, test them on real team problems, and recommend what works.

Conditions

Remote first. The role can be performed remotely from anywhere in the US or Canada, regardless of the location listed.

US salary range: $175,000 to $218,000 USD. Canada salary range: $171,500 to $202,500 CAD.

Final pay depends on your background, job-related knowledge, skills, and experience. US base pay may vary by one of three geographic tiers.

Interviews may include AI-assisted tasks, or exercises done without AI. Your recruiter will explain what applies at each stage. Undisclosed AI use that was not discussed with or approved by your recruiter may affect your candidacy.

The company uses AI to make hiring more efficient, but people on the hiring teams make every hiring decision.

The company is an equal opportunity employer and does not discriminate on any legally protected basis. Candidates who do not meet every qualification are encouraged to apply.

Benefits

• Total pay includes restricted stock units (RSUs) along with a full benefits package.
• US employees get medical, dental, vision, life, and disability insurance, paid 100% by the company. Canadian employees get life and disability cover, plus supplemental medical and dental plans.
• US employees get a 401(k) with company matching. Canadian employees get an RRSP with a DPSP.
• Paid parental leave.
• Mental wellness program and employee assistance program.
• Flexible paid time off, company holidays throughout the year, and summer and winter shutdowns.
• Learning and development programs.
• Equipment, tools, and support for setting up a productive home office.
• A free premium membership to the family app and free tracking devices.