Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Kubernetes @ 2
Python @ 6
Statistics @ 3
Airflow @ 2
Algorithms @ 3
Machine Learning @ 3
scikit-learn @ 6
Azure @ 2
Mathematics @ 3
Databricks @ 2
Pandas @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
You’ll help Eneco navigate volatility, risk, and opportunity in the evolving energy market. As a Fundamental Analyst you will build fundamental machine learning models and algorithms that operate in fast-moving, real-time energy markets, collaborating closely with teams across Trading, Forecasting, IT, and Operations.
Responsibilities
- Explore large datasets (granular weather forecasts, renewable generation data, real-time order book updates) to uncover patterns that predict price movements and grid imbalances.
- Develop live signals, robust price forecast models, and intuitive dashboards for traders.
- Build decision-support tools that run in production and iterate models based on immediate market feedback.
- Take full ownership of the full model lifecycle: research, development, deployment, and day-to-day maintenance.
- Backtest and validate trading ideas to assess risk and profitability before going live.
- Translate quantitative signals into automated strategies and conduct post-trade analysis to quantify execution performance.
Requirements
- Quantitative MSc or PhD in Econometrics, Mathematics, Statistics, Computer Science, Physics, or a related field.
- 5+ years of experience in a quantitative role (experience in Intraday Power markets or other energy commodities preferred).
- Strong Python proficiency (expert in data manipulation with Pandas, NumPy) and comfortable with statistical/modeling libraries (Scikit-learn, Statsmodels).
- Solid grounding in statistics and time-series analysis.
- Familiarity with parts of the tech stack: Azure Cloud, Kubernetes, Databricks, Airflow.
- Pragmatic, result-oriented mindset; able to deliver models that are performant enough for real-time markets.
Where you’ll work
You will work within the Intraday Trading team as part of the value chain Trading & Structuring, right next to Rotterdam-Alexander station. The role is in a complex, dynamic environment with close collaboration between traders and analysts.
What we have to offer
- Gross annual salary between €85.000 and €120.000 (including FlexBudget and 8% holiday allowance; depending on role a bonus or collective profit sharing).
- FlexBudget (can be paid out, used to buy extra holiday days, or saved).
- Personal and professional development support.
- Hybrid working: 40% at the office, 40% from home, and 20% flexibly. With manager approval, you may work abroad (within approved countries) up to 3 weeks/year, max 2 consecutively.
Technologies & Tools Mentioned
- Python, Pandas, NumPy
- Scikit-learn, Statsmodels
- Azure Cloud, Kubernetes, Databricks, Airflow
- Time-series analysis, machine learning, backtesting, dashboards