Our Client

eNordic is a Finnish energy platform dedicated to accelerating the green transition in the Nordics by developing and operating renewable energy infrastructure. With a strong local presence and deep industry expertise, E-Nordic focuses on long-term value creation through sustainable energy solutions. The company is backed by Ardian, a world-leading private investment house, whose support enables E-Nordic to scale its impact across the region and drive innovation in the energy sector.

Purpose

eNordic is looking for a Data Scientist to lead the work of leveraging their large portfolio of renewables to evaluate new investments to complement their portfolio. Investments into renewables - wind, solar, hydro and storage - is a space that is becoming increasingly data-driven. As such, Ardian decided to create its own data platform in 2020 to better determine where to best invest. The platform is called Opta, and it is at the absolute forefront of how to utilize data models for investments in renewables. By capturing data from a large fleet of renewables, markets and financial models, Opta is used to determine what projects best fit the reward and risk profile that Ardian is seeking. Determination is performed by running optimisation under a set of constraints which provides Ardian with a competitive edge in deal-making. Within Operations - post investment - Opta provides management teams and asset management teams with insights through monitoring and dynamic reporting to enhance performance. Now, Enordic wants to go even further by finding a data scientist to perform analyses that Opta is not yet capable of. This often means performing ad hoc analyses and working closely with our investment teams.

ABOUT THE ROLE

Working with eNordic, you will work with a very talented and motivated team, have access to massive amounts of data, and the results of your work will lead to investment decisions into sizable renewable energy projects. Your closest colleagues will be other data scientists who are also working on Opta.

You will be based in Gothenburg (Sweden) where your closest manager is based, and you will be expected to travel on a regular basis to meet investment professionals of Ardian and other Data Scientists. Most often this will be to where Ardian and Ardian affiliates’ offices are located in London, Madrid, Milan and Paris.

KEY RESPONSIBILITIES

• Build statistical, mathematical and machine learning models to assess the impact of (1) new investments or (2) changes in the current portfolio on the future cash flows and volatility of future cash flows of the renewable energy portfolio

• Work with investment teams and asset management teams to support investment or asset management decisions and identify the biggest opportunities to improve capital deployment and returns

• Draft presentations to share the analysis with the investment teams

• Work with the Opta product development team to update the calibrations of the models implemented in the Opta product

• Identify what parts of the analysis would benefit from being productized into Opta and work with the Opta development team to productize them

• Monitor and evaluate what new technologies, research, models could be used to improve the current methodology.

REQUIREMENTS

• A deep interest and curiosity in the intersection of renewables and data science

• Knowledge or prior experience of working with energy markets

• Experience and/or interest in investment topics will be appreciated

• Mastery of the main statistical, mathematical, machine learning, and deep learning models

• Excellent grasp of Python, Spark and git (feel free to detail in your application)

• Three years of relevant work experience

• Good understanding of cloud services (Microsoft Azure)

• Good understanding of BI tools

• Excellent communicator in written and oral English with ability to be didactic and to restitute complex modelling features into simple terms

• Ability to translate business needs into technical/mathematical solutions

• Project management capabilities

• High level of autonomy

• Familiarity with Microsoft Office suite

• Graduate from an Engineering or Business school with a degree in Mathematics, Statistics, Computer Science, Data Science, or similar field