Lead Data Scientist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Scientist based in United States.

This is a senior, hands-on data science opportunity focused on turning revenue opportunities into production machine learning systems. You’ll work across personalization, experimentation, subscriptions, transactions, and consumer advertising to support responsible, evidence-based growth. The role combines advanced statistical analysis, causal inference, experimentation, and production ML engineering. You’ll partner closely with Product, Engineering, Data Engineering, and MLOps teams to bring models into user-facing experiences. You’ll also help shape the roadmap for production ML while mentoring data scientists and establishing technical best practices. The environment is highly collaborative, product-minded, remote-first, and deeply integrated with generative AI. Your work will influence products serving more than 100 million monthly active users and directly contribute to measurable business outcomes.

Accountabilities

Investigate revenue-generating opportunities and analyze the underlying data to size, scope, prioritize, and measure product changes.
Design, build, deploy, and operate production ML systems, including batch inference, online services, and online learning models for personalization, experimentation, and automation.
Partner with Product, Mobile Engineering, Cloud Engineering, Data Engineering, and MLOps teams to integrate ML systems into customer-facing features.
Establish monitoring frameworks to evaluate the performance, reliability, and business impact of ML-powered experiences.
Implement data, code, and model lineage practices that support secure, reproducible, compliant, and maintainable ML lifecycles.
Collaborate with Data Engineering to improve the data ecosystem and pipelines that power experimentation and machine learning.
Apply causal inference, experimentation, and advanced analytics to guide product and monetization decisions.
Mentor other data scientists and help define best practices for advanced analytics, experimentation, and production ML development.
Use Claude Code and other AI tools throughout data discovery, modeling, coding, testing, and experiment evaluation.
Help establish and communicate effective AI-native workflows, raising the AI fluency and productivity of data science and engineering teams.
Work closely with business leaders to translate analytical findings into actionable product and revenue strategies.
Requirements
Advanced degree in a discipline requiring sophisticated statistical analysis, or equivalent professional experience.
6+ years of experience scoping, building, analyzing, and deploying ML-powered systems, including models shipped successfully to production.
Significant programming experience with Python, scikit-learn, PySpark, and causal inference tooling.
Strong understanding of software engineering practices, including testing, modularization, version control, and production-quality development.
Professional experience applying modern causal inference and causal analysis techniques.
Significant experience working with existing datasets, designing instrumentation to generate new data, and implementing transformations for complex analyses and ML development.
Hands-on experience designing, monitoring, and analyzing experiments within consumer technology environments.
Experience building ML systems or conducting experimentation within a B2C technology company, ideally involving subscriptions, transactions, advertising, or other revenue-generating products.
Strong communication and project leadership skills, with the ability to influence cross-functional teams and communicate complex technical concepts clearly.
A structured, hypothesis-driven approach to solving ambiguous problems using data and experimentation.
Experience using LLMs or generative AI for advanced data processing, analysis, development, or research workflows.
Experience with digital advertising and ad-tech infrastructure is highly desirable.
Familiarity with ranking and grouping algorithms for content feeds is a plus.
Experience contributing to or managing production feature stores and ML model registries is preferred.
Experience partnering with product-line general managers, including exposure to revenue reporting and forecasting, is advantageous.
Knowledge of subscription products, lifecycle marketing, user acquisition, geospatial data, or mobile location-based services is a plus.
Strong ownership mindset and ability to critically review AI-generated code, analyses, and models while remaining accountable for everything shipped.
Willingness to continuously experiment with emerging AI tools and turn useful discoveries into repeatable team practices.
Benefits
Annual base salary of $175,000–$218,000 USD, with final compensation determined by experience, skills, background, and geographic location.
Equity compensation through Restricted Stock Units (RSUs).
Medical, dental, and vision insurance, with plans fully paid for U.S. employees.
Life and disability insurance and additional supplemental benefit options.
401(k) plan with company matching.
Paid parental leave.
Mental Wellness Program and Employee Assistance Program (EAP).
Flexible paid time off, companywide holidays, and summer and winter shutdowns.
Learning and development programs to support ongoing career growth.
Equipment, tools, and reimbursement support for an effective remote working environment.
Remote-first work culture.
Complimentary premium membership and connected-device benefits.
An AI-native working environment where modern AI tools are integrated into data discovery, development, experimentation, and everyday productivity.
An inclusive, mission-driven culture that values direct communication, integrity, customer impact, and high-impact execution.