Data Scientist

We are looking for an analytical and proactive Data Scientist to join our growing Vaisala Xweather team in Keilaniemi, Espoo. Xcast Sensors  form the critical hardware foundation of our Xweather solutions, powered with hyperlocal, real-time weather and environmental data (Xcast - Weather forecasting technology). Deployed in diverse settings – from roads and cities to remote energy infrastructure – these sensors are essential to enabling new data-driven business models and driving actionable insights across industries. 

Vaisala itself is a global leader in measurement instruments and intelligence helping industries, nations, people, and the planet to thrive. From predicting hurricanes to optimizing renewable energy production, our technology is used where it matters the most – from data centers, windfarms and laboratories to airports, the Arctic and even the surface of Mars. Vaisala is recognized in TIME Magazine’s World’s Best Companies in Sustainable Growth 2025 study. Our team of over 2,400 experts and 59 nationalities around the world is committed to taking every measure for the planet. Driven by our shared purpose, curiosity, and pioneering spirit, we stay ahead and make a difference. At Vaisala, you don’t have to fit in to belong. 

Why join us?

• Drive real-world impact by applying machine learning to solve complex time-series and structured data challenges that support climate resilience and sustainability. 

• Collaborate across disciplines with scientists, engineers, designers, and commercial experts to turn data into actionable insights in a fast-growing, purpose-driven product environment. 

• Shape the future of data science at Xweather, where innovation meets mission—helping build smarter, safer solutions for a changing world.  

What will you do? 

As the Data Scientist, you will help in advancing our applied machine learning capabilities. You will focus on exploring and developing new features, testing a variety of modeling approaches, and supporting innovation in how we use supervised learning for complex time-series and structured data challenges. You will report to the Chief Science Officer. 

Key Responsibilities:  

• Design and test features for supervised learning models, including temporal and metadata inputs. 

• Experiment with a range of modeling techniques to evaluate performance. 

• Explore methods to support both deterministic and statistical approaches to prediction. 

• Contribute to reproducible research practices, including consistent metrics and evaluation. 

• Collaborate with engineers to integrate promising approaches into larger workflows. 

What will you bring: 

• Hands-on experience with machine learning libraries (scikit-learn, XGBoost, PyTorch, TensorFlow, or similar). 

• Strong skills in feature engineering for time-series or structured datasets. 

• Familiarity with statistical and ensemble methods. 

• Proficiency in Python, with strong analytical and data manipulation skills. 

• Interest in working with large, real-world datasets. 

For additional information, please contact the hiring manager, Scott Mackaro at [email protected]. Please note that applications sent via email cannot be processed due to privacy reasons. 

Ready to take every measure for the planet? Apply at the latest on December 3rd, 2025 via the application form.