FinOps Data Scientist, Global Services Security - Office of Security Innovation
DESCRIPTION
As a Data Scientist within the Global Services Security organization, you will support efforts for internal AWS account infrastructure resource and cost optimization. In a large organization including many thousands of builders, it is important to accurately and efficiently track, maintain, and optimize usage of AWS fleet resources.
This is an exciting opportunity to leverage advanced analytics and data engineering at the intersection of cloud and infrastructure optimization. Your primary responsibility will be to design and implement sophisticated data pipelines, conduct complex statistical analyses, and develop scalable business intelligence solutions that drive actionable insights for our fleet management efforts. You will have the opportunity to work with multiple lines of business and learn from (and contribute to) a variety of infrastructure optimization cases. This is a hands-on role where success is measured by delivering data-driven solutions that have measurable business impact.
Key job responsibilities
- Partner with business and finance teams to identify high-impact data-based opportunities and develop robust data engineering solutions from proof-of-concept to production-ready systems
- Design and implement sophisticated ETL pipelines and data models that enable scalable analysis of fleet management data streams
- Conduct complex statistical analyses and hypothesis testing to validate assumptions and identify new opportunities for data-driven solutions
- Develop advanced visualization solutions and automated reporting systems that effectively communicate insights to various stakeholders
- Create and maintain production-quality statistical models for anomaly detection, time series forecasting, and pattern recognition in financial and security contexts
- Build and optimize data pipelines and warehousing solutions to improve efficiency of data investigation and delivery
- Collaborate with engineering teams to integrate data-backed solutions into large-scale, highly complex production services
- Establish best practices for data governance, documentation, and knowledge sharing across teams
About the team
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BASIC QUALIFICATIONS
- Bachelor's degree and 5 years of experience or Master's degree and 2 years of experience
- SQL experience, including complex queries, optimization, and data modeling
- Python experience with focus on data libraries (pandas, numpy, scipy) and visualization libraries (plotly, bokeh, Streamlit)
- Background in statistics and experimental design
- Experience building and maintaining data pipelines and ETL processes at scale
PREFERRED QUALIFICATIONS
- Experience with modern data warehouse solutions (Redshift, Security Lake) and data lake architectures
- Expertise in statistical modeling, A/B testing, and causal inference
- Proficiency with BI tools (Amazon QuickSight) and ability to design scalable dashboarding solutions
- * Experience with distributed computing frameworks (Spark, Hadoop, Amazon EMR)
- Background in anomaly detection, time series analysis, or pattern recognition
- Experience with cloud infrastructure (AWS preferred) and data engineering best practices
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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