Join Ezpada’s Data Science team and help build tools and models that support analysis and decision-making in European energy and commodity markets.
Who are we? Ezpada Group was founded in April 2004 as a privately held company focused on the wholesale trading of electricity with physical delivery and financial settlement, as well as network capacity, coal, oil, gas, and emission allowances. We operate on global commodity markets, with a strong and diversified presence across the European energy landscape.
Our trading activities are coordinated from our trading floors in Zug (Switzerland), Houston (Texas), London (UK) and Germany, supported by our teams based in Prague (Czech Republic). Ezpada currently employs more than 140 professionals from a wide range of countries.
We possess an in-depth understanding of the energy sector, built on many years of trading experience and the continuous expansion of our strategic network.
What You Will Be Responsible For:
Develop data-driven models and analytical tools to support trading and market analysis in European energy markets
Build forecasting and predictive models using historical market data, fundamentals, and external datasets
Work closely with traders and analysts to translate market insights into quantitative models
Develop tools that allow traders to analyze market scenarios and identify trading opportunities
Deploy analytical models into production pipelines and maintain them over time
Improve and refactor the existing codebase to enhance performance and maintainability
Build dashboards and reporting tools to communicate analytical insights to traders and analysts
Contribute to the architecture and development of the team’s data science platform
Collaborate with data engineers and IT on data infrastructure and pipelines
Tech Stack/Tools You Will Work With:
Python (pandas, numpy, scikit-learn or similar)
SQL
Streamlit and Power BI for data visualization
Airflow for workflow orchestration
Git for version control
Nice to Have:
Experience with time series analysis, forecasting, or machine learning
Experience working with large market datasets
Familiarity with model deployment or data pipelines
Knowledge of European energy or commodity markets
We welcome applications from candidates with different levels of experience. The candidate’s experience and suitability for the role will be evaluated throughout the recruitment process.
What will you get from Ezpada in return?
Meaningful work that directly influences trading decisions.
Autonomy to lead initiatives and make impactful technical decisions.
A collaborative, high-performing team culture.
Hybrid work model with a modern office in the heart of Prague.
Weekly team breakfasts and regular team-building events.
Personal development budget and financially supported, in-person language courses (English, Czech, German) held on-site.
... in the Box Do you consider yourself to be a Demand Forecasting Model expert and enthusiast? Then this position might be the perfect fit for you! As a Senior Data Scientist, Demand Forecasting, you will play a pivotal role in designing, implementing, and improving our demand forecasting time series and causal models that ...
... national or international networks relevant to data science, phenomics, and biomedical analytics. Candidate profile This position is well suited to a senior scientist with a strong background in computational biology, bioinformatics, biostatistics, data science, AI-driven biomedical analysis, or a related discipline, who ...
... intelligent, AI-powered capabilities that help users gain deeper insights, automate routine work, enhance productivity, and create a more seamless work experience. As a Data Scientist in the Work Intelligence Unit, you will play a key role in product development through the application of state-of-the-art AI and machine learning technologies ...
... do eksploracji danych oraz rozwiązań wykorzystujących sztuczną inteligencję. Ukázat vše (9) O pozici / o projektu Původní popisek. Poszukujemy doświadczonego Data Scientista do międzynarodowego projektu realizowanego dla dużej organizacji sektora publicznego na poziomie europejskim. Osoba na tym stanowisku będzie odpowiedzialna ...
... Work with the latest technology stack: Azure, Databricks, PySpark, and latest AI tooling - Keep humans in the loop — validate model and agent output, and uphold data governance standards - Make a tangible impact on the shopping experience of millions of customers What do we expect from you? - Enthusiastic Data Scientist willing ...
Hledáme zkušeného Data Engineera, který se zapojí do rozvoje datového prostředí a bude mít možnost ovlivnit způsob, jakým jsou data získávána, zpracovávána a připravována pro další využití. Čeká Vás práce s daty z různých systémů, vývoj datových pipeline a datové modelování v cloudovém prostředí. Součástí role je také spolupráce ...
... datových pipeline a integraci dat z různých SaaS a podnikových systémů. Budete mít prostor podílet se také na návrhu datové architektury a rozvoji moderního data stacku. Náplň práce: - Návrh, vývoj a správa škálovatelných ETL/ELT pipeline pro data z různých zdrojů, včetně SaaS platforem, ERP, CRM a databází. - Vývoj a ...
... Váš profil: o Bakalářský titul v oboru informatiky, datového inženýrství nebo příbuzného oboru. o Více než 5 let zkušeností s cloudovými platformami pro big data, nejlépe Azure nebo GCP. o Praktické zkušenosti s Databricks, Delta Lake a Spark; znalost Kafka, Flink nebo podobných frameworků je výhodou. o Zkušenosti s budováním ...
... only” are more than just words? Then join Processand, one of the leading implementation partners for Celonis – Process Intelligence. Your mission As a Data Scientist, you will transform business process data into actionable insights that shape our clients’ digital transformation journeys. You’ll take ownership of data-driven ...
We're looking for a Middle+ Data/Databricks Engineer to join our data team and take ownership of pipelines built on Databricks. You'll design and run production-grade ETL/ELT workloads, work with the lakehouse (Delta Lake) architecture, and partner closely with analysts, data scientists, and business stakeholders who rely ...