Head Data Scientist

Job Responsibilities

• Use knowledge of utility data, organizations and priorities to advise clients on data-driven solutions to operational needs, regulatory mandates, and customer outreach.
• Leverage knowledge of the electricity and gas sector to select appropriate statistical and technical approaches to client challenges.
• Prepare reports, presentations, tools, and proposals explaining technical analytical methods and results to both technical and non-technical audiences.
• Familiarity with the full data science stack, with a focus on machine learning, data visualization and communication of complex results to a variety of audiences
• Write production-level machine learning pipeline code
• Create and provide guidance on solution architectures including integration with Amazon Web Services (AWS) and /or Azure.
• Project manage and/or support teams to deliver high quality analysis while remaining on time and on budget.
• Take initiative to validate and troubleshoot data and statistical models.
• Coach junior staff to develop their data science skills.
• Define hiring needs, and support recruiting, hiring, and onboarding of new team members.
• Lead meetings, conference calls, and email exchanges with clients
• Track energy industry trends and emerging issues
• Other duties as assigned.

Job Requirements

• A Bachelors degree in a quantitative field is required; a Master’s Degree is strongly preferred.
• A minimum of 7+ years of work experience in one or more of the following disciplines: data science, economics, statistics, public policy with a quantitative focus, or computer science
• Experience performing advanced customer data analytics, including propensity modeling and high frequency consumption data analysis
• Substantial work experience in the energy and utilities sector
• Practical experience in machine learning, applied econometrics and/or statistical program evaluation
• Real world experience scraping and/or munging large data sets
• Significant programming experience using R, Python and SQL to build and deploy regression, classification, and other statistical models.
• Experience building machine learning pipelines.
• Strong written and oral communication skills
• Experience with model selection and validation methods
• Strong data visualization skills
• Understanding of relational databases and basic architectural principles
• Experience with AWS and/or Azure to deliver data-driven solutions.
  
• AWS certifications are highly preferred.
• Experience using Tableau or other data visualization software
• Familiar with the use of version control (e.g. git/GitHub)
• Project management experience, including supervising junior staff and tracking budgets and deliverables, preferably in a consulting or client-facing environment.