Power Data Scientist

Marlin Selection Ltd; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Marlin Selection Ltd seeks an expert in ML-driven forecasting to develop and productionise time-series models for energy generation. You will build forecasting pipelines, collaborate with data engineering to onboard data feeds and monitor quality, and analyse power market fundamentals to improve model features.

The role also involves maintaining dashboards and providing technical modelling support to analysts and key stakeholders in a fast-paced energy trading context.

Qualifications

• PhD or equivalent in ML, data science, statistics, mathematics or similar.
• Experience building production-grade ML models with MLOps, Git and CI/CD.
• Strong Python programming with Pandas, Scikit-learn and PyTorch or Keras/TensorFlow.
• Experience developing time-series forecasting models in data-rich environments.
• Knowledge of SQL; Databricks experience is advantageous.

Responsibilities

• Develop, enhance and productionise ML time-series forecasting models for energy generation.
• Build, automate and maintain forecasting pipelines for traders.
• Collaborate with data engineering to onboard new data feeds and monitor data quality.
• Analyse power market fundamentals and add features to forecasting models.
• Maintain dashboards and reports and provide modelling support to analysts.

Skills

Time-series forecasting

Machine learning

Python

MLOps

Git

CI/CD

Pandas

Scikit-learn

PyTorch

Keras/TensorFlow

Education

PhD or equivalent in a quantitative field

Tools

Databricks

Job description

• Developing, enhancing and productionising machine learning time-series forecasting models, with an initial focus on wind and solar generation.
• Building, automating and maintaining forecasting pipelines to ensure accurate, reliable and timely model outputs for traders.
• Collaborating with data engineering teams to onboard new data feeds, monitor data quality and continuously improve model performance.
• Analysing power market fundamentals and incorporating new features into forecasting models as renewable generation evolves.
• Maintaining dashboards and reports while providing technical modelling support to analysts and key stakeholders.

You will need to have the following:

• A PhD or equivalent advanced qualification in Machine Learning, Data Science, Statistics, Mathematics or another quantitative discipline.
• Experience building and deploying production-grade machine learning models, with a solid understanding of MLOps, Git and CI/CD practices.
• Strong Python programming skills, including experience with Pandas, Scikit-learn and either PyTorch or Keras/TensorFlow.
• Proven experience developing time-series forecasting models, ideally within energy, commodities, financial markets or another data-intensive environment.
• Knowledge of SQL is essential, with experience of Databricks and exposure to energy or commodity trading considered advantageous.

Please complete the form below, your data is processed here under legitimate interest. Please also note that for your privacy no data from this form is stored in this website ( view our privacy policy ).