Senior Data Scientist / ML Engineer (Process Industry)

Near U Ltd; Spain; Remote; EUR 70,000 - 98,000; Full time

Job summary

Near U Ltd is seeking a Senior Data Scientist / ML Engineer with hands-on experience in process-industry production data to join our international team on an industrial production analytics project. You will develop predictive models to optimise processes, improve quality and reduce downtime, working remotely with colleagues in the EU.

Based in Portugal or other EU countries, you will travel occasionally to the UK.

Qualifications

• Degree in Data Science, Computer Science, Engineering, Mathematics, Physics or similar.
• Senior-level hands-on experience developing predictive models in process-industry environments.
• Strong Python skills and practical ML / predictive modelling experience.

Responsibilities

• Develop, validate and improve predictive models on production, process, sensor and time-series data.
• Build solutions for process optimisation, quality and scrap prediction, anomaly detection and predictive maintenance.
• Independently own analytics and modelling workstreams from data exploration to model delivery.
• Work closely with the team and customer process experts to understand production challenges.
• Communicate findings and recommendations clearly to customer stakeholders.
• Contribute to a good team spirit and share knowledge to improve the team.

Skills

Python

ML modelling

Pandas

Scikit-learn

XGBoost

LightGBM

PyTorch

TensorFlow

Education

Degree in Data Science or related field

Tools

OSIsoft PI

AVEVA

Azure ML

Databricks

MLflow

Job description

We are Near.U. We strive to develop our solutions by following the best practices of our craft. That means building robust, well-tested and maintainable models and code that deliver real, measurable value to our customers. We are looking to grow our team with a Senior Data Scientist / ML Engineer with hands‑on experience in process-industry production data.

You will join an existing international team on an industrial production analytics project. You’ll develop predictive models that help customers in industries such as pulp & paper, steel and chemicals optimise their processes, improve quality and reduce downtime. This is a hands‑on Data Science / ML role. It is not focused on Data Engineering, BI or GenAI.

While working at MoOngy, you are expected to share your knowledge, and you’ll have the opportunity to learn new technologies and work on international projects. Our talent management program is tailor‑made to help you grow your career the way you envision it.

Please note: This position is primarily remote and open to candidates based in Portugal or the EU. Occasional travel to the UK, about twice during the initial assignment, is required. Start date: as soon as possible.

Moongy Group is an Equal Opportunity employer. All applicants will be considered without regard for race, colour, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion.

Responsibilities

• Develop, validate and improve predictive models on production, process, sensor and time‑series data
• Build solutions for process optimisation, quality and scrap prediction, anomaly detection and predictive maintenance
• Independently own analytics and modelling workstreams, from data exploration to model delivery
• Work closely with the existing team and customer process experts to understand production challenges
• Communicate findings, results and recommendations clearly to customer stakeholders
• Contribute to a good team spirit and share your knowledge to improve the work of others

Requirements

• Degree in Data Science, Computer Science, Engineering, Mathematics, Physics or similar
• Senior-level, hands‑on experience developing predictive models in process‑industry environments (pulp & paper, steel, chemicals or similar)
• Strong Python skills and practical ML / predictive modelling experience (e.g. pandas, scikit‑learn, XGBoost/LightGBM, PyTorch or TensorFlow)
• Solid experience with production, process, sensor and/or time‑series data
• Proven experience in at least one of: process optimisation, quality/scrap prediction, anomaly detection or predictive maintenance
• Autonomy and ownership of your own analytics and modelling work
• Strong professional English, written and spoken, with the ability to present findings to non‑technical stakeholders
• Availability to travel to the UK occasionally
• Nice to have: experience with industrial data platforms or historians (e.g. OSIsoft PI / AVEVA), cloud ML tooling (Azure ML, Databricks, MLflow), and previous consulting or customer‑facing experience

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