Junior Data Scientist – Energy AI & Optimization
Qcells
Santa Clara, CA
Description
POSITION DESCRIPTION:
We are seeking a motivated Junior Data Scientist (Temporary) to join our Grid & Energy Analytics team a short‑term assignment. This role is ideal for graduate students currently studying data science, computer science, engineering, or applied mathematics, who are excited about applying AI techniques to real‑world energy systems.
During this internship, the candidate will work closely with senior data scientists and the wholesale market applications team to build and fine‑tune energy AI agents, contribute to forecasting and optimization models, deploy AI models into production‑grade systems, and gain hands‑on exposure to state‑of‑the‑art research in energy optimization and agentic AI.
RESPONSIBILITIES
- Assist in building, fine‑tuning, and evaluating AI agents designed for energy forecasting, decision‑making, and optimization tasks.
- Support development of time‑series models for forecasting energy demand, solar generation, wholesale market prices, and ancillary services.
- Help explore and test new ML algorithms or MLOps architectures relevant to energy system challenges.
- Clean, preprocess, and analyze large‑scale energy datasets using Python‑based data science tools.
- Help evaluate model performance, perform error analysis, and implement incremental improvements.
- Work with senior engineers to package, test, and deploy AI/ML models in real operational environments.
- Assist in monitoring model performance and troubleshooting basic issues in production workflows.
- Stay up-to-date with emerging techniques in ML, forecasting, and AI agent design.
- Contribute to internal experiments investigating novel approaches for energy optimization and real‑time decision‑making.
- Collaborate with the data science team, wholesale market applications team, and software engineering teams.
- Present findings, experiments, and results in informal team updates.
REQUIRED QUALIFICATIONS
- Education - Currently enrolled in or recently completed an undergraduate or graduate program in data science, computer science, engineering, applied mathematics, statistics, or a related field.
- Basic proficiency in Python and common data science libraries (pandas, numpy, scikit‑learn, matplotlib).
- Familiarity with machine learning concepts (regression, classification, time‑series basics).
- Coursework or project experience in ML, AI, optimization, or statistics.
- Interest in learning about energy markets, renewable energy systems, and energy optimization.
- Strong curiosity and willingness to learn.
- Ability to work collaboratively with cross‑functional technical teams.
- Good communication skills and ability to present findings clearly.
- Self‑driven, organized, and comfortable with fast‑paced environments.
PREFERRED QUALIFICATIONS
- Familiarity with energy systems, renewable energy, or electricity markets.
- Exposure to deep learning tools (PyTorch, TensorFlow) or time‑series packages (nixtla).
- Experience with AI agents, reinforcement learning, or RAG pipelines.
- Previous internship or project experience with ML or MLOps tools.
- How real‑world energy AI agents are built and deployed.
- How production‑grade forecasting models are tested, scaled, and monitored.
- How the electricity grid, energy markets, and renewable assets interact.
- Best practices in software engineering, MLOps, and data science workflows.
- Exposure to cutting‑edge AI and optimization research used inside a global renewable energy company.
DURATION & STRUCTURE
- Flexible: 1 - 6 months
- Timing: May 19, 2026 – August 19, 2026
- Full‑time
PHYSICAL, MENTAL & ENVIRONMENTAL DEMANDS: To comply with the Rehabilitation Act of 1973 the essential physical, mental and environmental requirements for this job are listed below. These are requirements normally expected to perform regular job duties. Incumbent must be able to successfully perform all of the functions of the job with or without reasonable accommodation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
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The salary range is required by the California Pay Transparency Act and may differ depending on the location of those candidates hired nationwide. Actual compensation is influenced by a wide array of factors including but not limited to, skill set, education, licenses and certifications, essential job duties and requirements, and the necessary experience relative to the job’s minimum qualifications.
*This target salary range is for CA positions only and should not be interpreted as an offer of compensation.
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