Senior Data Scientist

Tech Talent Link

Job Overview:
Our client will be hiring a Senior Data Scientist with electrical engineering knowledge, advanced-level Python and intermediate SQL coding skills.
The ideal candidate will have worked at a tech company that is pushing the boundaries of data science or in the energy industry. Experience with optimization and advanced ML forecasting methods would also be ideal.
Report to the Sr. Director of Product Management.

***We are unable to work with 3rd-party or C2C candidates for this role***

  • In the first couple months, this position will set up ETL data pipelines, data visualization, analysis of data related to critical operational issues.
  • Redshift is the data warehouse solution that is used internally and offered to external customers. This position would need to access/cleanse/manipulate data in Redshift.
  • Longer term focus would focus on building predictive models related to battery performance/lifespan, creating forecasts that are an input into optimization models and control "apps".
  • Model and algorithm development
  • Work with Product to help prototype new analytics and optimization offerings
  • Conduct deep dive analyses of product challenges and opportunities; formulate conclusions and recommendations to be presented to senior leadership
  • Produce written recommendations and insights for key stakeholders that will help shape effective metric development and reporting
  • Simplify and automate reporting, audits, and other data-driven activities; build solutions to have maximum scale and self-service ability by stakeholders


  • 5+ years of experience in predictive analytics or data science.
  • BSEE or Electrical Engineering background.
  • Advanced-level programming experience in Python.
  • Intermediate-level experience with relational databases – e.g. SQL, Redshift, Data Warehouse, etc.
  • An ability to thrive in a highly ambiguous, fast-paced and rapidly changing environment.
  • Energy storage or renewable energy industry experience is preferred.
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