Execute assigned tasks to assist in the development and maintenance of analytical models, dashboards, and reporting outputs.
Analyze datasets using established statistical techniques and basic machine learning methods to support defined analytical objectives.
Apply foundational modeling approaches, including string‑matching and reconciliation techniques, to structured analysis tasks as directed.
Prepare intermediate analytical outputs (tables, summaries, visualizations) for review and iteration.
Execute data cleaning and transformation in Python or R, following established ETL and data processing workflows.
Draft clear summaries of findings and document data sources, assumptions, and methodologies in accordance with team standards.
Prepare charts, tables and dashboards visualizations to support stakeholder understanding and decision-making.
Support collaboration with internal teams and project stakeholders by gathering requirements and clarifying data needs.
Participate in code reviews, documentation reviews and team knowledge-sharing activities.
Assist with maintaining organized project files, analysis artifacts, and reference documentation.

A bachelor’s degree.
A minimum of 2 years of relevant work experience.
1 year of Python experience, including libraries like pandas, numpy, and scikit-learn.
Experience building basic dashboards or reports using BI tools (Tableau preferred).
Experience developing analytical models or performing structured data analyses using a high-level programming language.
Foundational knowledge of descriptive and introductory inferential statistics.
Familiarity with common machine learning techniques and basic understanding of data warehousing concepts and ETL processes.
Ability to work effectively on a team, manage individual work streams, and explain analytical results clearly to various audiences.
A technical test will be required during the interview process.

Data Scientist I, Solar Programs

Key skills