Fortinet is seeking a Staff Data Scientist to leverage advanced data science techniques to drive insights, optimize product workloads, and enhance infrastructure efficiency.
Requirements
- 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
- Experience with data pipelines (e.g., Airflow, Spark)
Responsibilities
- 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.
Other
- 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.
- Strong communication skills
- BS/MS/Ph.D. in quantitative field
