Staff Data Scientist, Product Efficiency & Data Infra

Fortinet-posted 4 months ago
$190,000 - $230,000/Yr
Full-time • Senior
Santa Clara, CA
51-100 employees
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We are seeking a highly skilled Staff Data Scientist to join our Product Workload & Efficiency Engineering team. This role will focus on leveraging advanced data science techniques to drive insights, optimize product workloads, and enhance infrastructure efficiency. The ideal candidate is a strategic thinker with a strong technical background, exceptional communication skills, and a proven track record of delivering data-driven solutions in a fast-paced environment.

  • Partner with product, engineering, finance, sales, and customer success teams to model and forecast product workloads, define metrics, and build tools for planning.
  • Design experiments and studies to reduce uncertainty in workload forecasts and optimize product/revenue flows.
  • Analyze data to address business questions, generate insights using statistical methods, and present findings to stakeholders.
  • Architect data models, pipelines, and applications to support workload data, finance and infrastructure teams.
  • Develop and productionize metrics and dashboards for system availability, reliability, and performance.
  • Conduct root cause and causal inference analyses of availability issues, recommending remediations.
  • Shape data science areas like segmentation, recommendation systems, forecasting, and cost prediction.
  • Analyze product usage to identify growth drivers and improvement opportunities.
  • Manage stakeholders, define project OKRs, and communicate results effectively.
  • Mentor team members and champion evidence-based decision-making with self-service data products.
  • Represent data science across the organization and at conferences.
  • Bachelor’s or higher in a quantitative field (e.g., Statistics, Math, Computer Science, Engineering).
  • 8 -10+ years in analytics driving business decisions (e.g., product/marketing analytics, business intelligence).
  • Proven ability to work independently and engage stakeholders proactively.
  • Expertise in SQL, large datasets (e.g., Hadoop), statistical analysis, and techniques like regression.
  • Experience with optimized data formats for analytics, such as Parquet, and potentially Apache Iceberg.
  • Expertise in defining schemas, managing metadata, and crawling data sources.
  • Proficiency in writing complex SQL queries to analyze data stored in S3-based data lakes.
  • Integrate dbt with orchestration tools like Apache Airflow to automate, schedule, and monitor data pipelines that feed machine learning models.
  • Proficiency in Python and strong communication skills.
  • 7+ years in data science/ML in high-growth tech.
  • Expertise in system reliability metrics, data pipelines (e.g., Airflow, Spark).
  • Familiarity with product analytics.
  • Strong coding (e.g., Python) and cross-functional collaboration skills.
  • BS/MS/Ph.D. in quantitative field.
  • Medical, dental, vision, life and disability insurance.
  • 401(k).
  • 11 paid holidays.
  • Vacation time and sick time.
  • Comprehensive leave program.
  • Participation in the Fortinet equity program.
  • Bonus eligibility reviewed at time of hire and annually.
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