Data Scientist

TLDR

Contribute to the growth of MET Energia Italia by developing data-driven solutions, predictive models, and actionable insights for strategic decisions in the energy sector.

As we continue to evolve our client portfolio and expand, MET Energia Italia is now looking for a talented Data Scientist, who will be contributing to the growth of the company in the Italian market.

In this role, you will be responsible for managing, analysing, and interpreting large datasets from external providers and markets, with a primary focus on the power and gas commercial portfolio. You will develop predictive models and data‑driven solutions that support strategic and operational decisions related to consumption forecasting and market‑oriented optimization strategies.

Step by step you will take on several activities that are part of the main duties within the Portfolio team, bringing your invaluable contribution to our daily operations:

  • Collect, clean, validate, and integrate large datasets from multiple internal and external sources (markets, forecasting services, metering data, commercial systems)
  • Analyze, manipulate, and process high‑volume datasets using statistical and programming tools
  • Develop and maintain statistical models, machine learning algorithms, and predictive analytics to forecast energy demand, prices, imbalance risks, and portfolio behavior
  • Design and implement dashboards, data visualizations, and KPI monitoring tools to provide actionable insights to internal stakeholders
  • Perform scenario analysis and simulations to support strategic decisions, risk assessment, and commercial optimization
  • Deliver clear, structured presentations of analytical results and recommendations to management and cross‑functional teams
  • Supporting the launch of new ideas and projects to grow the business
  • Be active and ready to take on new challenges in other areas of MET should this become your desire
  • BSc or MSc in Data Science, Mathematics, Statistics, Economics, or Physics, with a strong academic track record
  • 3-5 years of relevant experience, preferably within the energy industry (electricity, gas, and renewables)
  • Proficiency in Python, R, and SQL
  • Solid experience in time-series forecasting, statistical modeling, and the use of machine learning libraries
  • Hands-on experience with Databricks and Apache Spark for large‑scale data processing, and familiarity with cloud environments (Azure, AWS, or GCP)
  • Strong data visualization skills and experience creating clear, insightful dashboards using modern BI tools (e.g., Power BI, Tableau).
  • Ability to communicate complex insights clearly, both visually and verbally
  • Sharp analytical mindset and strong problem‑solving orientation
  • Proven ability to work collaboratively in multidisciplinary environments
  • Proactive, results-driven, and able to thrive in a fast-paced environment
  • Well organized, autonomous with time management and planning skills
  • Fluent in Italian with a strong command of English
  • Proficient in MS Office, with advanced Excel skills for analysis and reporting

In this role, you will have the opportunity to make a big impact to the overall results of the company. You will be part of a dynamic, innovative growth company which embraces new ideas and encourages everyone to contribute to our strategy.

We have an open, informal culture and we trust our people to get the job done - so we will also give you plenty of autonomy.

You will be working in an international environment which creates opportunities to share knowledge and work together with colleagues from other MET subsidiaries, mainly from the Swiss office.

MET Group is an integrated European energy company that operates across natural gas, power, and renewable energy markets. Serving customers in 21 countries, it focuses on multi-commodity wholesale trading and energy infrastructure, making a strong impact in the transition to greener energy solutions. With extensive experience and a significant presence in various national markets, MET is well-positioned to support the evolving energy landscape.

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