Principal IoT Data Scientist – Predictive Analytics

Pale Blue Dot Recruitment; Galway; On-site; EUR 70,000 - 90,000; Full time

Job summary

Pale Blue Dot Recruitment is seeking a Data Scientist for a ten-month contract based in Galway. You will lead end-to-end data science projects on connected-product and telemetry data to improve product performance and customer operations.

The role involves working with large IoT datasets, applying ML, statistical modelling and data exploration techniques to real engineering and operational challenges. Independent, principal Data Scientist on assigned projects is expected.

Qualifications

• Degree or master’s qualification in Data Science, Mathematics, Physics, Computer Science, Engineering or a related discipline.
• Approximately three to five years of professional experience in an applied Data Science or Machine Learning role.
• Strong experience developing supervised machine-learning and predictive-modelling solutions.
• Practical experience working with structured time‑series, telemetry, sensor or other machine‑generated data.
• Advanced SQL skills, including independently exploring large datasets and combining data from multiple sources.
• Strong Python skills for data manipulation, statistical analysis and machine learning. Relevant experience using R may also be considered.
• Experience with feature engineering, model selection, validation and evaluation.
• Experience addressing imbalanced datasets, anomaly detection or rare‑event prediction.
• Good understanding of machine‑learning techniques used for classification, regression, clustering and anomaly detection.
• Ability to manipulate, analyse and visualise both structured and unstructured datasets.
• Proven ability to take an ambiguous business or engineering problem from initial concept through to a practical, evidence‑based solution.
• Strong communication and data‑visualisation skills, including the ability to convert analytical findings into clear explanations and recommendations.
• Experience leading projects and estimating the resources and timelines required to deliver analytical solutions.
• Experience developing predictive‑maintenance, reliability, survivability or equipment‑failure models.
• Experience working with IoT, connected‑product or industrial telemetry data.
• Understanding of Tableau or a comparable data‑visualisation platform.
• Experience supporting the deployment or scaling of machine-learning models within production environments.
• Understanding of automotive engines, refrigeration systems, industrial equipment or machine‑performance data.
• Previous experience working with engineering, manufacturing or product‑development teams.

Responsibilities

• Develop supervised machine-learning models for predictive maintenance, equipment failure prediction, anomaly detection and operational optimisation.
• Carry out feature engineering, model selection, validation and performance evaluation.
• Develop appropriate approaches for imbalanced datasets, rare failure events and incomplete or uncertain ground-truth data.
• Apply statistical inference and supervised and unsupervised machine-learning techniques to identify meaningful patterns and predict equipment behaviour.
• Transform analytical outcomes into scalable and optimised solutions suitable for always‑on production environments.
• Independently explore large structured IoT, telemetry, time-series and sensor datasets using advanced SQL.
• Identify relevant signals and create reliable modelling datasets by joining, cleaning and aggregating information from multiple sources.
• Investigate data quality, availability and limitations before selecting an appropriate analytical approach.
• Manipulate and visualise structured and unstructured datasets.
• Establish suitable ground truth by working with engineering teams and investigating equipment behaviour, operating conditions and historical events.
• Take ownership of Data Science projects from initial problem definition through data investigation, modelling, evaluation and communication of results.
• Lead assigned projects, including defining scope, estimating timelines and coordinating activities with cross‑functional contributors.
• Communicate findings, limitations and recommendations clearly to engineering teams, customers and other stakeholders.
• Operate effectively as the principal Data Scientist without requiring day‑to‑day technical direction or mentoring from another Data Scientist.
• Use cloud technologies, machine-learning techniques and statistical models to generate insights, improve predictability and support optimisation at scale.
• Collaborate with product, engineering, data engineering, software and DevOps teams to define problems and design analytical solutions.
• Translate analytical findings into clear metrics, visualisations and practical recommendations.
• Support the development and deployment of reliable, scalable Data Science solutions.
• Document analytical methods, assumptions, model performance and conclusions.
• Promote recognised industry practices in Data Science, machine learning and statistical analysis.
• Communicate the value and practical application of Data Science and machine learning to technical and non‑technical audiences.
• Contract Information: Location Galway; Working arrangement Full‑time contract.

Skills

Python

SQL

Time-series

Data visualization

Machine learning

Education

Data Science degree

Mathematics/Physics/CS/Engineering

Tools

Tableau

R

Job description

Pale Blue Dot Recruitment is seeking a Data Scientist for a ten-month contract based in Galway. You will lead end-to-end data science projects on connected-product and telemetry data to improve product performance and customer operations.

The role involves working with large IoT datasets, applying ML, statistical modelling and data exploration techniques to real engineering and operational challenges. Independent, principal Data Scientist on assigned projects is expected.