PPC Trading – Energy Data & AI Senior Manager

PPC Trading – Energy Data & AI Senior Manager

The world of energy is constantly evolving, creating new challenges and opportunities for those who want to make a difference. At PPC Group, we believe the future is shaped by people who want to grow, innovate, and make a real impact.

PPC Trading, a member of PPC Group, is driving the transition toward a modern, technologically mature energy trading model where data analytics and Artificial Intelligence are leveraged for decision-making and capitalising on opportunities in a dynamically shifting energy landscape.

If you want to shape the future of Powertech with us, apply now by sending your CV to [email protected]!

Responsibilities:

• Contributes to shaping and detailing the Data & AI strategy for energy markets, aiming to leverage data and artificial intelligence to support energy market operations and ensure full alignment with trading objectives and risk management.
• Evaluates, tests, and proposes the adoption of new technologies, innovative energy data sources, and state-of-the-art Machine Learning/AI models, in cooperation with relevant central teams to build a competitive advantage.
• Participates in the design, customisation, and optimisation of data pipelines (ETL/ELT) and ML pipelines to meet the needs of energy markets as well as for the collection, processing, and utilisation of data related to energy prices, demand, generation, RES, load, cross-border flows, power plant availability, and other market fundamentals, ensuring reliable data flow from source to production in collaboration with relevant central Data/IT teams.
• Implements advanced AI models and develops agentic AI workflows, leveraging approved enterprise AI platforms and architectures to automate complex analytics, support decision-making, and deliver intelligent tools to Trading and Analytics teams.
• Applies centrally defined Data Governance and MLOps principles to guarantee data and model quality, integrity, and security across their entire lifecycle.
• Actively monitors energy markets and generates advanced analytics, forecasts, and actionable insights for Traders and Senior Management using both statistical methods and AI techniques.
• Works closely with trading desks to understand their needs and build tailored dashboards and real-time analytics tools that directly support daily operations.
• Coordinates daily operations and provides technical guidance to BI Analysts and Data Engineers, while supporting the management of complex Data & Analytics projects, including engagement with external vendors.

Requirements:

• Bachelor's degree or diploma) from a Greek or foreign University, preferably in Engineering, Computer Science, or a Bachelor of Science.
• A Master’s degree (MSc) in Data Science, Artificial Intelligence, Big Data Analytics, Applied Mathematics/Statistics, Computer Science, or Software Engineering will be an asset.
• At least eight (8) years of proven professional experience in one or more of the core areas below, including at least two (2) years in roles with team management duties:
• End-to-End Data Pipelines: Design, development, and maintenance of ETL/ELT data pipelines in production environments. Cloud Services: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP), focusing on storage services (e.g., S3, Blob Storage), databases (e.g., RDS, BigQuery), and data processing services (e.g., Glue, Data Factory, Databricks).
• ML Model Development & Deployment: Practical experience in the development, training, and production deployment of Machine Learning models.
• Programming & Databases: Proficiency in Python, utilising libraries such as Pandas, Scikit-learn, TensorFlow/PyTorch, and SQL. Solid experience with relational (e.g., PostgreSQL) and non-relational (NoSQL) databases.
• Experience in one or more of the following areas will be an asset:
• Trading or Energy Markets: Domain experience in the energy sector, financial markets, or algorithmic trading.
• Agentic AI Flows & LLMs: Experience in designing and developing agentic AI workflows or leveraging Large Language Models (LLMs) to automate complex tasks.
• MLOps: Experience with MLOps practices and tools for automating the Machine Learning model lifecycle (e.g., MLflow, Kubeflow, SageMaker Pipelines).
• Big Data & Streaming: Hands-on experience with distributed data processing engines (e.g., Spark) and real-time streaming platforms (e.g., Kafka, Flink).
• Business Intelligence & Dashboards: Experience with Business Intelligence tools (e.g., Power BI, Tableau, Looker) for developing dynamic dashboards that support decision-making.
• Proven track record in big data analysis, visualisation projects, time-series forecasting projects, optimisation models, and statistical modelling will be an asset.
• Knowledge in one or more of the following areas will be an asset: Knowledge of Data Warehouse design and DevOps/MLOps practices.

Competencies:

• Accountability and Result Orientation
• Problem Solving and Decision Making
• Understanding of the business environment
• Effective Team Management
• Negotiation & Influencing skills
• Change Management

Benefits:

• Attractive benefits package
• Development opportunities in a constantly evolving environment
• Possibility of flexible work arrangements
• Inclusive work environment