Data Science Intern

We are Lightsource bp – and we’re on a mission to become a global leader in onshore renewables, anchored by our proven track record in solar development.

For over a decade we’ve been actively working to diversify the way our world is powered with sustainable and responsible renewable power. We work to safely deliver affordable, reliable, large-scale onshore renewable and energy storage solutions to help the world decarbonise.

Our growing business is constantly innovating and investing to help drive the energy transition. Our people and projects are focused on supporting long-term sustainable growth and energy security.

Lightsource bp operates with five core values: Safety, Integrity, Respect, Sustainability, and Drive.

We seek to attract and hire individuals who share our commitment to creating a safe workplace, uphold the highest standards of integrity, and demonstrate respect for colleagues, communities, and the environment. Our recruitment process promotes sustainability by valuing long-term growth and responsible practices, while seeking candidates with the drive to innovate and lead in the global energy transition.

Together, these values shape how we engage, assess, and welcome talent to join us in delivering transformational solar power solutions worldwide. 

Lightsource bp was fully acquired by bp in 2024.

What you’ll do (the role)

Summary

As a Data Science Intern at Lightsource bp, you will work on high‑impact optimisation and decision‑science problems that underpin our energy storage and grid‑integration strategy. You’ll contribute to research, design, experiment, implement and test approaches (modelling, simulation, reinforcement learning and optimization) that support improved operational decision‑making for battery energy storage systems (BESS).

This internship is designed for a PhD‑level researcher who wants to apply cutting‑edge methods to real‑world energy systems within a global renewable energy organisation.

At Lightsource bp, our Applied AI team is building the next generation of intelligence that powers renewable energy systems at global scale. As part of this team, you won’t just contribute to your research—you’ll see your work shape real‑world optimisation, operational decision‑making, and the future of grid‑interactive storage. We invest heavily in developing exceptional technical talent, offering exposure to high‑impact projects, collaboration with experienced AI practitioners, and opportunities to publish, innovate, and drive our AI roadmap forward. Joining us means growing your career in an environment where deep technical expertise is valued, ambitious ideas are encouraged, and your contributions help accelerate the energy transition.

The Details

Duration: 1 June – 21 August 2026 (12 weeks)
Location: London or Milan (Hybrid Working – 3 days per week in office)
Type: Full-time internship
Education Required: Currently pursuing a PhD (or final-year PhD candidate) in a quantitative field; Master's degree required as minimum

We also consider alternative educational paths if you can demonstrate equivalent experience in RL, optimisation, or advanced machine learning.

Responsibilities of the Role

• Develop and evaluate reinforcement learning (RL), (constrained) optimisation, or simulation models to support BESS dispatch strategy.
• Prototype algorithms for sequential decision‑making under uncertainty, incorporating market, operational, and physical system constraints.
• Analyse large time‑series and operational datasets to extract actionable insights that support energy trading, grid services, and storage optimisation.
• Collaborate closely with data scientists and product teams to design experiments and validate models.
• Communicate findings clearly to both technical and non‑technical stakeholders through documentation, visualisations, and presentations.
• Contribute to reproducible, high‑quality research code and experimentation pipelines.
• Stay current with emerging methods in RL, optimisation, and energy systems research.

Why you’ll make a great member of the team

Experience & Knowledge Required

• Experience conducting research or applied work in one or more of: reinforcement learning, control systems, (constrained) optimisation, probabilistic modelling or simulation.
• Strong understanding of sequential decision‑making frameworks (e.g., MDPs, policy optimisation, planning).
• Experience working with large datasets, experimental design, and empirical model evaluation.
• Understanding of numerical methods, statistical learning, or stochastic processes.
• Familiarity with energy systems, grid flexibility markets, or storage optimisation is a plus but not mandatory.

Skills Required

• Strong proficiency in Python and its scientific computing toolkit (JAX, Pyomo, NumPy, Scipy, Statsmodels, Pandas/Polars and similar).
• Solid knowledge of PyTorch, Gymnasium and one or more of the following reinforcement learning frameworks: StableBasleine3, TorchRL, RLlib, SKRL.
• Ability to design and evaluate RL agents or optimisation algorithms.
• Strong analytical and mathematical reasoning skills.
• Ability to communicate complex technical findings clearly and concisely.
• Ability to within a production-grade codebase.
• Experience with scientific coding best practices (version control, experimentation tracking, reproducibility).
• Ability to work in a research environment while following agile ways of working (i.e. continuous iterative delivery and improvement).
• Curiosity, autonomy and good organizational and time management skills.

Education Required

• Currently pursuing a PhD (or in the final years of a PhD) in Machine Learning, Computer Science, Applied Mathematics, Engineering, Operations Research, or a related quantitative field.
• Master’s degree in a relevant discipline required.
• We consider other educational paths provided the candidate can demonstrate extensive experience in one or more of the areas mentioned before.

Why you’ll want to work for us

Our company is a place where you can be yourself and grow, a place where your ideas and opinions matter.

Be you: We pride ourselves on being an inclusive community, where every individual is valued and treated with respect.

Be responsible: Our culture is driven by our core values – from operating safely to ensuring our projects are responsible. 

Be recognized: Alongside a competitive salary, we offer a variety of benefits including annual bonus, retention bank, health insurance, pension and other local benefits.

Be inspired: Beyond your day-to-day working life at Lightsource bp, there’s a variety of initiatives that will contribute to your own personal development. These include our charitable causes, supporting our solar honey project, or volunteering on our VIBES committee to name a few.

Our core values: Lightsource bp truly cares about creating a sustainable future through safe, responsible and meaningful low carbon energy projects. Our core values of Safety, Integrity, Respect, Sustainability and Drive are the guiding principles for everything we do. 

For further information on our career opportunities and life at Lightsource bp, please visit https://www.lightsourcebp.com/careers/