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Snap Inc.
Snap Inc.
5,001 – 10,000 Employees
ConsultingLogisticsMarketing
Snap Inc. is a technology company building camera-driven products for communication, creativity, and self-expression. Its work centers on using visual technology to help people connect while considering the broader effects of digital products on mental health, society, and the environment. The company also highlights diversity, equity, and inclusion across its workforce, responsible design, ethical governance, transparent decision-making, and environmentally conscious operations.
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Lead Data Scientist, Core — Los Angeles (Onsite)

Lead experimentation, causal inference, machine learning, and scalable data products for Snap’s Core organization in Los Angeles.

USUnited StatesCACaliforniaNYNew YorkWAWashington
$229,000 – $343,000 / year
On-siteFull-timeSeniorEnglish RequiredData Scientist
PythonSQL

Description

  • Serve as the organization’s subject matter expert in experimentation and causal inference methods.
  • Direct medium- to large-scale initiatives involving teams and stakeholders across the organization.
  • Design, build, and maintain scalable statistical, machine learning, and data products for internal tools.
  • Turn complex statistical principles into OKR-aligned strategies that inform executive decisions.
  • Foster a collaborative, inclusive, supportive, and engaging team environment.
  • Partner with product managers, engineers, and researchers on problem-solving and analytics studies.
  • Analyze diverse data sources, test hypotheses, uncover patterns, and add business context to findings.
  • Lead recurring insight presentations that bring the consumer perspective into organizational decisions.
  • Execute the data science and analytics roadmap through ongoing improvement, reporting, and measurement.
  • Set strategic direction, clarify projects, advise on methodology, and communicate results.
  • Promote a culture centered on quality, innovation, and experimentation.
  • Apply AI tools to create scalable data solutions while preserving accuracy and statistical rigor.

Requirements

  • Bachelor’s degree in statistics, mathematics, economics, computer science, engineering, another relevant quantitative or technical discipline, or equivalent practical experience.
  • At least 7 years of post-bachelor’s experience in quantitative analysis or data science; alternatively, a relevant master’s degree with 6+ years of postgraduate experience or a related PhD with 3+ years of postgraduate experience.
  • Advanced knowledge of statistical analysis techniques.
  • Experience with computational tools such as Python libraries including SciPy, statsmodels, and EconML, or equivalent R-based ecosystems.
  • Demonstrated ability to turn data into actionable insights and opportunities that improve growth and performance.
  • Strong command of predictive modeling, machine learning, experimentation, and causal inference.
  • Expertise designing and working with data orchestration pipelines.
  • Advanced Python or R skills and strong SQL proficiency.
  • Clear communication skills and meticulous attention to detail.
  • Ability to independently initiate projects and carry them through completion.
  • Ability to reconcile practical business requirements with scientific rigor.
  • History of achieving end-to-end adoption through stakeholder input and iterative product development.
  • Willingness and ability to learn and apply evolving AI systems and tools.
  • Preferred: advanced degree in a quantitative or technical discipline.
  • Preferred: experience managing a team focused on data capture, measurement, and optimization.
  • Preferred: experience building partnerships with cross-functional leaders.
  • Preferred: product experience in social media, online advertising, digital media, or mobile technology.
  • Preferred: experience applying causal inference models, advanced statistical methods, and large-scale A/B testing.

Benefits

  • Paid parental leave.
  • Comprehensive medical insurance coverage.
  • Programs supporting emotional and mental well-being.
  • Compensation structures that enable employees to participate in Snap’s long-term success.
  • Restricted stock units as part of the equity offering.

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