Senior Data Scientist
Unikie · Tampere, FI
Job description
WE ARE LOOKING FOR
Senior Data Scientist
We're looking for a Senior Data Scientist who turns industrial data into operational decisions - not just models, and not just dashboards. You'll lead data science work in real production environments across heavy industry, chemicals, manufacturing, logistics and energy. The hard part here isn't fitting a model: it's figuring out what to predict, from what data, and whether it's worth doing at all. This is the role for someone who has seen projects stall because the team modelled whatever data happened to be available - and wants to solve that properly.
What you'll do:
- Assess data sources, quality and gaps to determine what is realistically predictable - and demand the right enrichments and history before modelling
- Predict machine failure and maintenance needs (RUL, lifecycle), and optimize production efficiency, energy use and operational flows
- Combine predictive models with optimization to turn forecasts into prioritized actions - an approach we call Composite AI: the model predicts, optimization decides under real constraints, and the output is a decision, not just a score
- Scope problems with clients using a structured method (CRISP-DM or equivalent) - business and data understanding before modelling
- Assess feasibility: define use cases, KPIs and a high-level business case, and recommend the data, instrumentation or process changes needed
- Build interpretable models that support diagnostics and operational decisions Work hands-on with modern AI tooling and agentic workflows - we expect our data scientists to use the best tools, not just talk about them
Skills Required
- Python
- SQL
- Data Science
Locations
- Tampere
REQUIRED QUALIFICATIONS
- 5+ years in data science, ideally with industrial, manufacturing or process-industry use cases
- Process-industry data sense: you read production data in its process context, not just as statistical signals
- A structured, methodical approach you actually follow - you don't jump straight to the model
- Strong Python and SQL, solid time-series analytics, and comfort taking models toward production
- Experience with anomaly detection, clustering and deep learning for sensor data
- A communicative, proactive working style - you engage stakeholders and translate operational reality into data requirements
- Familiarity with cloud platforms (AWS or Azure)
- Bonus: mathematical optimization (LP/MIP, e.g. CPLEX / CP Optimizer), combining predictive ML with optimization, R, and prior work with manufacturing or industrial clients
WHY JOIN UNIKIE?
We are dedicated partner for global players in our segments – Unikie supplies technology solutions and services to several global Fortune 500 companies in EMEA and America.
As a responsible and competent partner, we have access to some of the most interesting projects. Technology we create enables our clients to become digital leaders in their own industries.
We cherish transparency and do our best that it shows up in as many processes as possible. One example of this is our salary model.
We have top-notch technical talent, dedication and excitement to develop ourselves and solve even the toughest challenges.
The combination of our agile teams, proven track record, industry insight, and holistic service and solution model place us at the forefront of cutting-edge technologies.
Work in a flexible low-hierarchy organization that looks after its own.
Unikie is a global software engineering and innovation company that infuses intelligence into machines, vehicles, and industrial solutions. We provide intelligent solutions for the automotive, heavy equipment, transportation & logistics, devices & IoT, and networks & communication industries.
With over 500 engineering professionals and a revenue of 65 million euros (2023), Unikie is a premium partner for unique embedded software and marshalling solutions that create value and success in the evolving digital landscape of tomorrow.
ML/AI Work links you to the employer's original posting — always verify the details there before applying.
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