Lead Data Scientist — Causal ML & Insights (Equity)

Snap Inc.; Bellevue (WA); On-site; USD 229,000 - 343,000; Full time

Benefits offered by this job

Paid parental leave

Comprehensive medical coverage

Emotional and mental health support

Equity/RSUs

Job summary

Snap Inc. is seeking a Lead Data Scientist to advance analytics and data-driven decision making. You will act as SME for experimentation and causal inference, lead cross-functional projects, and architect scalable data products that empower internal tooling and strategic initiatives.

The role emphasizes translating statistical insights into actions and partnering with product, engineering, and research teams to uncover product opportunities and drive growth.

Qualifications

• Bachelor's degree in a technical or quantitative field or equivalent experience.
• 7+ years of post-Bachelor’s experience in quantitative analysis and/or data science; or a Master’s +6+ years; or PhD +3+ years.

Responsibilities

• Act as the organization SME for experimentation and causal inference methodologies.
• Lead medium to large projects across multiple groups and stakeholders.
• Architect, implement, and maintain scalable data products and internal tooling.
• Translate complex statistics into strategic approaches aligned with OKRs.
• Collaborate cross-functionally with PMs, engineers, and researchers to identify opportunities.
• Drive insights sharing and analytics studies to shape product strategy.

Skills

Advanced statistics

ML modeling

Causal inference

Data pipelines

SQL

Python

Communication

Project management

AI tools awareness

Education

Bachelor's degree in statistics/Math/CS/Engineering

Master’s degree in a relevant field

PhD in a related field

Tools

Python

SQL

SciPy

statsmodels

EconML

R (ecosystem)

Job description

Snap Inc. is seeking a Lead Data Scientist to advance analytics and data-driven decision making. You will act as SME for experimentation and causal inference, lead cross-functional projects, and architect scalable data products that empower internal tooling and strategic initiatives.

The role emphasizes translating statistical insights into actions and partnering with product, engineering, and research teams to uncover product opportunities and drive growth.