Lead Data Scientist — Causal ML & Insights Leader

Snap Inc.; New York (NY); Hybrid; USD 229,000 - 343,000; Full time

Benefits offered by this job

Equity (RSUs)

Job summary

Snap Inc. is seeking a Lead Data Scientist to drive experimentation and causal inference across multiple teams in NYC.

You will architect data products, translate complex analyses into business actions, and lead collaborations with product, engineering, and research to shape product strategy. The role emphasizes building scalable analytics, delivering regular insights, and maintaining rigorous statistical standards while leveraging AI tools to enhance data solutions.

Qualifications

• Strong background in statistics and data science.
• Experience with predictive modeling and ML.
• Proficiency in SQL and Python or R.
• Ability to lead cross-functional projects and communicate insights.

Responsibilities

• Act as subject matter expert for experimentation and causal inference.
• Lead medium to large data science projects across teams.
• Architect and maintain scalable data products and tooling.
• Translate statistical findings into strategic business actions.
• Foster an inclusive, high-performance team environment.
• Collaborate with product managers, engineers, and researchers to identify opportunities.
• Analyze data sources and provide business context for decisions.
• Lead insights share-outs to drive consumer voice in the org.
• Deliver on data science roadmap with reliable reporting and metrics.
• Provide strategic direction and rigorous methodology while ensuring quality.

Skills

Statistics

ML modeling

Causal inference

Experimentation

SQL

Python

R

Data pipelines

Communication

Project management

Education

Bachelor's degree in a technical field

Master's degree (preferred)

PhD (preferred)

Tools

SciPy

statsmodels

EconML

Job description

Snap Inc. is seeking a Lead Data Scientist to drive experimentation and causal inference across multiple teams in NYC.

You will architect data products, translate complex analyses into business actions, and lead collaborations with product, engineering, and research to shape product strategy. The role emphasizes building scalable analytics, delivering regular insights, and maintaining rigorous statistical standards while leveraging AI tools to enhance data solutions.