Data Scientist

Summary

GroundWork Renewables is the solar industry’s trusted full-stack performance partner, delivering precise MET data and PV module insights. As a Data Scientist, you will collaborate with engineering, laboratory, and operations teams to design and deliver robust data systems, ensuring data reliability and accessibility.

Responsibilities

• Technical Subject Matter Expertise: Design, implement, and maintain relational and time-series databases for lab instrument data, environmental measurements, and operational records. Develop and manage ETL/ELT pipelines to ingest, transform, and store data from IoT sensors, measurement hardware, and remote sensing platforms. Build and deploy data access APIs and web applications using modern tools (e.g., Streamlit, FastAPI, React, or similar frameworks) to enable parent company analysts and stakeholders to query, visualize, and export lab data. Apply AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude) to accelerate software delivery while maintaining code quality and auditability appropriate for a laboratory environment
• Data Quality Assurance & Control: Develop and enforce QA/QC protocols to validate incoming data from lab instruments and field sensors in accordance with applicable regulatory and accreditation standards (e.g., ISO 17025 or similar). Implement automated checks, flagging routines, statistical validation, and audit trails to detect anomalies, missing data, and calibration drift. Maintain defensible data records that satisfy chain-of-custody and traceability requirements. Ensure data integrity from acquisition through delivery to downstream consumers
• Database Architecture & Optimization: Architect and optimize database schemas for performance, scalability, and ease of access. Evaluate and recommend appropriate database technologies (SQL, NoSQL, time-series) based on data volume, query patterns, and reporting requirements of the lab and parent company
• Stakeholder Collaboration: Partner with lab scientists, operations, and parent company data teams to understand data access requirements and translate them into technical solutions. Serve as the primary point of contact for data availability and reporting needs
• Web Application Development: Design and build web-based data access tools, dashboards, and reporting interfaces using modern full-stack frameworks (e.g., React, FastAPI, Streamlit, Plotly Dash). Leverage AI-assisted development environments (e.g., GitHub Copilot, Cursor, Claude Code, or similar) to accelerate development cycles while ensuring maintainability, security, and compliance with lab data governance requirements. Enable non-technical users at the parent company to explore, filter, and export lab datasets through intuitive interfaces without requiring direct database access
• Data Governance & Documentation: Maintain comprehensive data dictionaries, schema documentation, and data lineage records consistent with laboratory quality management systems. Contribute to laboratory SOPs and data management plans. Stay current with emerging data engineering technologies, AI tooling, and laboratory informatics practices to continuously improve the lab’s data infrastructure

Skills

• Minimum of 2 years of experience in database engineering, data software development, or a related technical discipline, preferably in a laboratory, scientific, or renewable energy context
• Bachelor's degree in computer science, software engineering, information systems, data science, or a related field
• Proficiency in SQL and experience with relational databases (PostgreSQL, MySQL, or similar); familiarity with time-series or NoSQL databases a plus
• Proficiency in Python (pandas, SQLAlchemy, FastAPI, or similar) for data engineering, scripting, and backend service development
• Experience building web applications or data dashboards using tools such as Streamlit, Dash, FastAPI, React, or modern AI-assisted development environments (e.g., GitHub Copilot, Cursor, Claude Code)
• Experience implementing QA/QC workflows for scientific or sensor data, including anomaly detection, validation rules, statistical flagging, and audit logging
• Excellent communication skills; ability to translate complex technical data concepts for non-technical stakeholders including lab scientists and business analysts
• Familiarity with version control (Git), CI/CD practices, and cloud data platforms (AWS, Azure, or GCP); experience with containerization (Docker) is a plus
• Demonstrated experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code, or similar) to write, debug, and refactor code
• Understanding of laboratory informatics concepts and data management in accredited or regulated settings
• Experience in photovoltaic (PV) testing, solar energy measurement, or a physical laboratory environment is highly preferred
• Advanced degree or relevant certifications preferred
• Familiarity with laboratory quality management standards (e.g., ISO 17025, GLP, or similar regulatory frameworks) is a strong plus
• Experience with LIMS (Laboratory Information Management Systems) or similar platforms is a plus

Qualifications

Must Haves

• Minimum of 2 years of experience in database engineering, data software development, or a related technical discipline, preferably in a laboratory, scientific, or renewable energy context
• Bachelor's degree in computer science, software engineering, information systems, data science, or a related field
• Proficiency in SQL and experience with relational databases (PostgreSQL, MySQL, or similar); familiarity with time-series or NoSQL databases a plus
• Proficiency in Python (pandas, SQLAlchemy, FastAPI, or similar) for data engineering, scripting, and backend service development
• Experience building web applications or data dashboards using tools such as Streamlit, Dash, FastAPI, React, or modern AI-assisted development environments (e.g., GitHub Copilot, Cursor, Claude Code)
• Experience implementing QA/QC workflows for scientific or sensor data, including anomaly detection, validation rules, statistical flagging, and audit logging
• Excellent communication skills; ability to translate complex technical data concepts for non-technical stakeholders including lab scientists and business analysts
• Familiarity with version control (Git), CI/CD practices, and cloud data platforms (AWS, Azure, or GCP); experience with containerization (Docker) is a plus
• Demonstrated experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code, or similar) to write, debug, and refactor code
• Understanding of laboratory informatics concepts and data management in accredited or regulated settings

Nice to Haves

• Experience in photovoltaic (PV) testing, solar energy measurement, or a physical laboratory environment is highly preferred
• Advanced degree or relevant certifications preferred
• Familiarity with laboratory quality management standards (e.g., ISO 17025, GLP, or similar regulatory frameworks) is a strong plus
• Experience with LIMS (Laboratory Information Management Systems) or similar platforms is a plus