Siemens Energy

A Snapshot of Your Day

As a master’s thesis student at Siemens Energy, you will investigate how to make pricing recommendation models not only statistically accurate but also business reliable. You will explore advanced smoothing and hybrid forecasting techniques to minimize the defect rate — the percentage of price recommendations deviating more than ±8% from actual transaction prices — while maintaining sound accuracy (low MAE and MAPE). Your work will directly support data-driven decision-making in pricing and competitiveness strategies across Siemens Energy’s service and product portfolio.

How You’ll Make an Impact

• Analyze the relationship between traditional machine learning accuracy metrics (MAE, MAPE) and business metrics such as defect rate in historical pricing data.
• Evaluate and tune hyperparameters of smoothing models (SES, Holt–Winters, LOWESS, Savitzky–Golay, and hybrid quantile-cap methods) to minimize both error and defect rate.
• Develop an adaptive optimization framework that combines statistical and business objectives into a single multi-criteria evaluation.
• Investigate new or hybrid models (e.g., state-space models, gradient boosting regressors, or lightweight RNNs) that enhance price stability and competitiveness.
• Deliver actionable insights, model comparisons, and parameter guidelines for implementation in Siemens Energy’s digital pricing systems.

What You Bring

• Strong background in data science, machine learning, statistics, or applied mathematics.
• Hands-on experience with time series forecasting, smoothing models, and Python-based analytics (statsmodels, scikit-learn, pandas, NumPy).
• Understanding of model evaluation metrics such as MAE, MAPE, and business KPIs.
• Analytical and structured mindset with interest in optimization and applied modelling.
• Motivation to balance technical accuracy with real-world business impact.
• Proficiency in English and ability to communicate findings effectively to both technical and business audiences.

About the Team

Within our team, you will work alongside a wide spectrum of disciplines. Expect day-to-day collaboration with solution architects, ontology specialists, and data scientists with deep expertise in data architecture and advanced analytics, as well as mechanical and quality engineers who know every nut and bolt of our products. This cross-functional setting immerses you in a global company at the forefront of new-energy technology and gives you the chance to build a professional network that can drive future collaborations and career opportunities.

Our Gas Services division offers Low-emission power generation through service and decarbonization. Zero or low emission power generation and all gas turbines under one roof, steam turbines and generators. Decarbonization opportunities through service offerings, modernization, and digitalization of the fleet.

Who is Siemens Energy?

At Siemens Energy, we are more than just an energy technology company. With ~100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation. 

Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation. 

Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideo

Our Commitment to Diversity

Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.

Application

Don’t hesitate – apply via the Apply button, id nr 285818 no later than 2025-12-14.

Ongoing selection is applied, the role might be filled before last application date.

For questions about the role, please contact hiring manager Davood Naderi on davood.naderi@siemens-energy.com

For questions about the recruitment process please contact the responsible recruiter Ermina Imamovic on ermina.imamovic.ext@siemens-energy.com

We refrain from all contact with staffing and recruitment companies, or advertising brokers.

Location: Finspång

Trade Union Representatives:
Unionen, unionen.finspang.se@siemens-energy.com
Sveriges Ingenjörer & SACO, asi.se@siemens-energy.com
Ledarna, Anders Fors, anders.fors@siemens-energy.com
IF Metall, Mikael Malmgren, mikael.malmgren@siemens-energy.com

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