Data Scientist

HERO Recruitment; Galway; Hybrid; EUR 65,000 - 90,000; Full time

Job summary

HERO Recruitment is seeking a Data Scientist for a hybrid Galway role, focusing on predictive analytics and machine learning in an industrial IoT context. You will own end-to-end projects, from data exploration to deploying validated models, directly influencing product decisions and customer outcomes.

You will work with large telemetry datasets, build robust models, and collaborate with engineering teams to translate complex problems into data-driven solutions, delivering clear insights and

Qualifications

• 3–5 years commercial experience in Data Science or Machine Learning.
• Experience building supervised ML models using structured time-series or sensor data.
• Strong Python and advanced SQL skills.

Responsibilities

• Develop supervised ML models for predictive maintenance, anomaly detection and failure prediction.
• Explore and analyse large IoT/telemetry datasets using advanced SQL and Python.
• Engineer features from structured time-series data and build robust modelling datasets.

Skills

Python

SQL

Time-series data

Machine Learning

Feature engineering

Model validation

Data visualization

Cross-functional collaboration

Education

Master's in Data Science

Degree in Mathematics/Physics or related quantitative discipline

Tools

Pandas

Scikit-learn

Tableau

Job description

Data Scientist / Predictive Analytics & Machine Learning

Location: Galway (Hybrid) | 3–5 Years Experience

Contract role

We're partnering with an innovative engineering company that's using connected IoT and telematics data to transform how intelligent equipment is monitored, maintained and optimised.

This is a unique opportunity for an experienced Data Scientist to become the sole Data Scientist within the team owning projects end-to-end and developing machine learning solutions that have a direct impact on products, engineering decisions and customer performance.

The Role

You’ll work with large-scale telemetry and sensor datasets to build predictive models that solve real engineering problems. From exploring raw data through to deploying validated models, you’ll have the autonomy to shape solutions from the ground up.

What You’ll Do

• Develop supervised machine learning models for predictive maintenance, anomaly detection and failure prediction.
• Explore and analyse large IoT/telemetry datasets using advanced SQL and Python.
• Engineer features from structured time-series data and build robust modelling datasets.
• Select, validate and optimise models, including handling imbalanced datasets and rare failure events.
• Partner with engineering and product teams to translate complex problems into data-driven solutions.
• Communicate insights through clear visualisations and actionable recommendations.
• Lead projects independently from problem definition to delivered solution.
• 3–5 years commercial experience in Data Science or Machine Learning.
• Strong Python and advanced SQL skills.
• Proven experience building supervised ML models using structured time-series or sensor data.
• Hands-on experience with feature engineering, model validation and predictive modelling.
• Ability to independently investigate data, establish ground truth and evaluate model performance.
• Experience communicating technical findings to both engineering and business stakeholders.
• Degree or Master's in Data Science, Mathematics, Physics or a related quantitative discipline.

Nice to Have

• Experience with predictive maintenance or reliability modelling.
• Knowledge of anomaly detection, clustering or statistical inference techniques.
• Experience with Tableau or other data visualisation tools.
• Exposure to automotive, refrigeration, industrial equipment or IoT environments.