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Data Scientist – Enterprise Analytics and AI
| Company | Invenergy |
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| Location | Chicago, IL, USA |
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| Salary | $90000 – $117000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Mid Level, Senior |
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Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
- Minimum 4 years of experience in data science or machine learning roles, with a proven track record of delivering data-driven solutions; or, an advanced degree with 2+ years of experience.
- Fluency in Python, including data science libraries.
- Strong experience with SQL and working with large, complex datasets from various sources (e.g., structured, semi-structured).
- Familiarity with cloud-based platforms and tools for model deployment.
- Excellent problem-solving skills and the ability to clearly communicate technical concepts to non-technical stakeholders.
- Demonstrated experience with version control and collaborative development environments.
- Eligible to work in the United States without the need for employer visa sponsorship now or in the future.
Responsibilities
- Partner with internal stakeholders to identify and execute on high-impact opportunities for advanced analytics and machine learning applications.
- Communicate effectively with a wide range of audiences and business-domain experts on technical and non-technical topics.
- Design, develop, and deploy predictive models, machine learning models, deep learning models, statistical analyses, and optimization algorithms to support business operations across energy generation, storage, transmission, and corporate functions.
- Analyze large and complex datasets to extract actionable insights, identify trends, and present findings through compelling data visualizations and storytelling.
- Build scalable data pipelines and machine learning workflows in collaboration with data architecture and IT teams.
- Monitor and maintain the performance of deployed models and refine them over time as business needs evolve.
- Contribute to the development and adoption of enterprise AI/ML governance standards, model documentation, and best practices.
- Stay up-to-date with the latest tools, technologies, and trends in data science and AI to inform innovation and continuous improvement.
Preferred Qualifications
- Experience in the energy or utilities industry, particularly in renewables, grid operations, or asset management.
- Highly motivated and resourceful, able to independently solve open-ended problems with multiple constraints, ambiguity, and scale.
- Familiarity with time series analysis, geospatial data, and optimization techniques.
- Knowledge of MLOps principles and tools for managing model lifecycle and scalability.
- Experience with data visualization tools such as Power BI, Tableau, or Plotly.
- Exposure to LLM’s, computer vision, and reinforcement learning applications.
- Understanding of data governance, security, and compliance in enterprise environments.
