Data Science Manager
As a Data Science Manager, you will lead a team and do hands‑on work. You will work in a dynamic organization to turn data into actionable intelligence. The variety and complexity of challenges you will solve is second to none, but most important is the real world impact your work will have on the lives of millions of people.
The Data Science teams provide insights and conclusions from multiple sources of information in a variety of different formats using analysis techniques that range from simple to advanced. An ability to work cross‑functionally and on Agile teams is critical and you should have a broad knowledge of:
Statistical & Probabilistic Analyses
Programming/Software Development
Effective Visualization and Presentation
Key Accountabilities
Lead, manage, and mentor a team of Data Scientists
Employ sophisticated analytics programs, machine learning, and statistical methods for predictive and prescriptive modeling, forecasting, and simulations
Discover the best methods of integrating data from several different sources and formats for use in analyses
Project manage efforts both internal to the team and across the enterprise
Be intellectually curious and enjoy learning
Supervisory/Interpersonal- Experience Required
Can manage projects both internal to the team and across the enterprise.
Can supervise and mentor other team members.
Qualifications
4+ years of data science experience (energy sector is a plus)
Experience leading large projects and/or a team of individual contributors
Demonstrated ability to communicate and interact with business stakeholders without supervision
Demonstrated ability to translate technical knowledge into business terms
Fluency in:
Machine learning tools and technique
Python and/or R
SQL
Experience with cloud computing in Linux and Windows environments (Azure is a plus)
P.hD or Master’s degree in a quantitative discipline, exceptional candidates considered with Bachelor’s degree or Master’s degree in progress
Preferred Skills and Experience:
Strong background in full lifecycle of Data Science products
Knowledge of Agile frameworks
Active github repository and stackoverflow account
Interactive visualization tools (Power BI is a plus)
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