Senior Data Scientist / U
The Senior Data Scientist will design and deploy Python‑based machine‑learning models on production and sensor time‑series data to improve process efficiency and predict quality issues. They will independently own the analytics workflow, delivering actionable insights for anomaly detection, predictive maintenance, and scrap reduction to the industrial client.
Skills required
About this role
We are seeking a Senior Data Scientist to join our team and take ownership of analytics and predictive modeling activities for an industrial sector client. The project focuses on applying Data Science and Machine Learning to analyze and optimize production processes. You will work with production, process, sensor, and time-series data to develop practical ML solutions that support process optimization, quality and scrap prediction, anomaly detection, and predictive maintenance.
Main responsibilities:
- Develop and deploy predictive models using Python and practical ML techniques.
- Work with production, process, sensor, and time-series data to derive actionable insights.
- Focus on process optimization, quality/scrap prediction, anomaly detection, and predictive maintenance.
- Independently own analytics and modeling work, ensuring high-quality deliverables.
- Communicate findings and recommendations clearly to customer stakeholders in professional English.
Qualifications
Must have requirements:
- Process Industry Experience: Proven track record of applying ML to heavy/continuous manufacturing industries (e.g., pulp & paper, steel/metals, chemicals, refining, glass, or pharmaceuticals).
- Industrial Sensor & Time-Series Data: Demonstrated experience working with high-frequency, noisy historian/SCADA/telemetry feeds, sensor drift, missing data, and continuous time-series feature engineering.
- Core Predictive Use Cases: Hands-on experience developing and deploying models for at least two of the following:
- Scrap reduction & product quality prediction (soft sensors, virtual metrology)
- Process parameter optimization & yield maximization
- Asset health, anomaly detection, or predictive maintenance (PdM)
- Hands-on Python & ML Stack: Mastery of core Python data science libraries (pandas, polars, numpy, scipy), classical ML/gradient boosting (LightGBM, XGBoost, CatBoost, scikit-learn), and time-series packages.
- Autonomous Delivery & Client Facing: Proven ability to translate ambiguous operational problems into structured analytical tasks, work directly with plant engineers/operations stakeholders, and present findings clearly.
- Readiness to Travel: Willingness to travel to the UK approximately twice during the initial project phase.
- Fluent English and Polish.
Nice to have requirements:
- Experience with additional programming languages or data science tools.
- Familiarity with cloud platforms and services related to data science and machine learning.
- Advanced degrees or certifications in Data Science, Machine Learning, or related fields.
Additional Information
This position allows for remote work for candidates based in Poland.
Thank you for your interest in our offer. We will contact selected candidates whose experience best matches the requirements of the role.
Additional Information
We hereby inform you that Inetum Polska sp. z o.o. has implemented an internal reporting (whistleblowing) procedure. The content of the procedure and the possibility to submit an internal report are available at:
https://inetum.whispli.com/speakup?locale=pl
