BloombergNEF Quant Modeling Data Scientist

Key Skills

Data science techniques, Data Visualization, Effective communication skills, Machine learning techniques, NumPy, Pandas, plotly, PowerBI, Python Programming, SQL, Tableau, VBA

Job Description

You will be based in our London office as part of the Quant Modeling team at BloombergNEF – the world's leading independent provider of analysis tools, data, and research to decision-makers leading the future of energy. The Quant Modeling team supports the development and maintenance of models for BNEF’s sector and regional teams, focusing on the broader modeling and data science needs of BNEF’s business and analysis teams. By closely collaborating with sector and regional experts, we leverage vast datasets from BNEF and the Bloomberg Terminal to build innovative predictive models and analytics. Our work ranges from developing weather-driven energy forecasts to short-term price forecasting and advanced risk modelling. By implementing machine learning workflows and creating reusable Python modules, we ensure continuous model improvement and seamless integration with analyst workflows. Join us to be at the forefront of cutting-edge data science and deliver actionable insights that drive the global energy transition. 

BNEF Team Ethos:

To succeed at BNEF, we need people who can work independently and show initiative to develop their own viewpoints while being collaborative with colleagues. We look for innovative yet pragmatic thinking that turns big ideas into real insights and impact. Working at BNEF sometimes feels chaotic; we need teams that are both dynamic and structured to generate the unique perspectives our clients value. Our teams are diverse, creative, focused, and fun!

We'll trust you to:

• Develop and maintain predictive machine learning models for energy market analysis, including weather-driven power/gas demand forecasts, power outage predictions, and short-term price forecasting
• Assist in building reusable internal Python modules for energy-related quant research
• Implement and maintain automated machine learning models using tools like Airflow or Argo
• Conduct quantitative and qualitative research using data from the Bloomberg Terminal and internal databases to develop insights and analysis both internally and externally
• Effectively communicate research findings via intuitive interactive dashboards, reports, news stories, datasets, and direct client interactions
• Support internal and external stakeholder dialogues, to ensure our modeling pipeline remains relevant and adaptive
• Enhance and maintain popular legacy Excel-based client-facing quant models

You’ll need to have:

• A bachelor’s or master’s degree in a related field such as Data Science, Statistics, Computer Science, Engineering, or a related quantitative discipline
• Basic understanding of energy markets and the transition to a sustainable future or a strong willingness to learn
• Proficiency in Python and SQL; familiarity with machine learning libraries such as scikit-learn.
• A good understanding of Pandas and NumPy methods
• Strong quantitative skills and comfort with large datasets and complex models
• Good communication skills: writing (for model documentation and research, in English) and speaking (for presentations at conferences, to colleagues, or to clients)
• Good time management skills, initiative and ability to work on multiple projects at once

We'd love to see:

• Experience in using the Bloomberg Terminal (bdh, bdp, bql, bsrch etc.)
• Experience with data visualization tools like Tableau, Plotly-Dash, Power BI or Streamlit
• Experience using Excel-VBA and if possible, Python with Excel through xlwings
• Up to two years of experience in an analytical, data science or quant role

If this sounds like you:

Apply if you think we're a good match. We'll get in touch to let you know what the next steps are, but in the meantime feel free to have a look at this: https://www.bloomberg.com/professional