Sr. Data Scientist, AWS Data Center Infrastructure Operations

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, AWS, Machine learning techniques, Data science techniques, Business Intelligence, Data Visualization, MATLAB Programming, Data Modeling, R Programming, SAS, C# Programming, Data Engineering, Statistical modeling

Job Description

Are you interested in applying new methods to real world hard problems, and helping to drive changes in Data Center Operations? Do you want to play a key role in the future of AWS’s infrastructure? Come and join us!

The Central Infrastructure Analytics Team (CIAT) Data Scientist helps transform data into actionable insights for global teams by 1) interpreting the large data sets from a variety of internal sources to uncover the functional activity and implications 2) analyzing this data to discover patterns, trends and correlations 3) developing hypotheses and assisting in the design of experiments to explore these hypotheses and 4) developing and deploying actionable business intelligence solutions for the global customers. CIAT collects data from a myriad of internal systems. This data often require cleansing and interpretation in order to tell a functional story. Often, data from several sources must be combined to create a clear picture of the activities behind the data and provide a robust and reliable foundation for model development. The Data Scientist role is critical in transitioning the analysis output from Descriptive/Diagnostic to Predictive/Prescriptive, and providing the operations teams with actionable insights to enable ongoing improvements. The Data Scientist will use a variety of tools (e.g. Excel, Matlab, R, Python, SAS, SageMaker and SQL) to deep dive data sources to discover useful patterns that will drive process improvement or remediate systemic issues.

Key job responsibilities

In this role, you will apply advanced analysis techniques and statistical concepts to draw insights from massive datasets, build scalable machine learning models , and create intuitive data visualizations. You will contribute to each layer of the data solutions, working closely with Data Engineer, Business Intelligence Engineers and Global Process Owners to understand the business objectives, obtain relevant datasets and prototype predictive and prescriptive analytic models. You will review key results with business leaders and stakeholders, and you will work with your team to develop and deploy a productionized version of the model to your global customers. You are both pragmatic and scientific in your approach to data analysis and solution development.

About the team

The Central Infrastructure Analytics Team (CIAT) provides critical business intelligence services across a broad range of functions within the AWS global Data Center Community (DCC). Situated within Central Operations, CIAT is the analytics hub for Data Center based organizations, including but not limited to: Safety, Security, maintenance, daily operations, logistics, engineering and equipment management. CIAT is comprised of several specialty Builder functions including data engineering, business intelligence (visualization), systems engineering and data science. We build business intelligence solutions that drive right action at scale across our global data centers and supporting services.

BASIC QUALIFICATIONS

• Masters Degree
• 5+ years of experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems
• 5+ years of research experience in a quantitative filed
• 3+ years of experience investigating the feasibility of applying scientific concepts to business problems and products
• 5+ years of experience in the following skill(s): programming with a mathematical programming language such as R, MATLAB, or SAS or major programming language such as Python, Java, C++, C#, or C

PREFERRED QUALIFICATIONS

• Excellent verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts
• 10+ years of experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems
• 10+ years of research experience in a quantitative filed
• 5+ years of experience investigating the feasibility of applying scientific concepts to business problems and products
• 10+ years of experience in the following skill(s): programming with a mathematical programming language such as R, MATLAB, or SAS or major programming language such as Python, Java, C++, C#, or C
• PhD Degree or equivalent