Lead Data Scientist, Core, Level 6

Snap Inc.•Los Angeles, CA

4d•$195,000 - $343,000•Hybrid

About The Position

The Data Science and Insights team at Snap Inc. seeks to leverage massive data sets into actionable insights that deliver business value. As truth seekers and truth tellers, the team relays what the data says without bias, aiming to improve decision-making quality and speed across the organization to enable a deeper understanding of our customers and products. The team focuses on efficient and effective analytic execution, positioning themselves as go-to experts with deep knowledge and expertise, constantly striving for better, faster insights from data. Snap Inc. is a technology company that believes the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company operates Snapchat, a visual messaging app that enhances relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.

Requirements

Deep understanding of advanced statistical analysis, including expertise with modern computational packages (such as the Python libraries SciPy, stats models, and EconML, or equivalent R ecosystems)
Proven track record in transforming data into meaningful insights and opportunities to drive growth and performance
Strong knowledge of predictive modeling, machine learning, and experimentation/causal inference methods
Expertise in data orchestration pipelines
Expertise in SQL and advanced proficiency with Python or R
Excellent communication skills, with high attention to detail
Ability to initiate and drive projects to completion with minimal guidance
Ability to balance practical business needs and scientific rigor
Display a track record of driving end-to-end adoption through cycles of stakeholder feedback and product iteration
Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of data-driven decision-making, insights generation, and industry best practices
Bachelor's Degree in a relevant technical or quantitative field such as statistics, mathematics, economics, computer science, engineering or a related field or equivalent years of practical work experience
7+ years of post-Bachelor’s experience in quantitative analysis and/or data science; or a Master’s degree in a relevant field + 6+ years of post-grad experience in quantitative analysis and/or data science; or a PhD in a related field + 3+ years of post-grad experience in quantitative analysis and/or data science

Nice To Haves

Advanced degree in a quantitative or technical field (Economics, Statistics, Mathematics, Computer Science, Physics)
Experience leading a team responsible for data capture, measurement, and optimization
Experience forming partnerships with cross-functional leaders in engineering, product, design, research, etc.
Experience in a product-focused role at a social media, online advertising, digital media and/or mobile technology company
Experience with causal inference modeling, advanced statistical methods, and A/B testing at scale

Responsibilities

Act as the organization subject matter expert for key experimentation and causal inference methodologies
Lead medium to large projects encompassing multiple groups and stakeholders across the organization
Architect, implement, and maintain scalable, sustained statistics, ML, and data products for internal tooling
Translate complex statistical concepts into strategic approaches that directly align with organization OKRs and influence executive decision-making
Establishes a positive, mutually supporting, inclusive and fun team environment where every employee can do their best.
Work cross-functionally and partner with product managers, engineers, and researchers to solve problems, and conduct analytics studies to identify new product opportunities and shape product strategy
Conduct in-depth analysis of all data sources, asking the right questions, testing hypotheses, identifying patterns and providing the necessary business context to translate what it all means
Lead the development and implementation of regular insights share-outs that drive the consumer voice throughout the organization
Deliver on data science and analytics roadmap including continuous improvement, accurate and timely reporting and measurement
Provide strategic direction, project clarity, methodological consultation and deliver results
Drive and maintain a culture of quality, innovation and experimentation
Utilize AI tools to more efficiently develop scalable data solutions, while maintaining rigorous standards for accuracy and statistical integrity