Data Scientist

Data Scientist

Ten Month Contract

Pale Blue Dot® Recruitment is recruiting a Data Scientist for a ten-month contract with a leading global organisation based in Galway.

The successful candidate will join an EMEA Digital Solutions team responsible for using connected-product and telematics data to improve product performance, reliability and customer operations. This is a hands-on position for an experienced Data Scientist who can independently take an engineering or business problem from initial investigation through to a working analytical solution. The successful candidate must be comfortable operating as the principal Data Scientist on assigned projects, without relying on another Data Scientist for day-to-day technical direction.

Position Overview

Through the implementation of its telematics strategy, our client collects extensive machine, sensor and operational data from refrigeration units operating around the world. The Data Scientist will analyze this data to identify meaningful patterns, develop predictive models and create practical solutions that improve product performance and help customers manage their transport operations more efficiently and reliably.

The role involves working with large structured IoT and telemetry datasets and applying machine learning, statistical modelling and data exploration techniques to real engineering and operational challenges.

Core Areas of Responsibility

Applied Machine Learning and Predictive Modelling

• 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.

SQL Data Exploration and Feature Engineering

• 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.

End to End Project Ownership

• Take ownership of Data Science projects from initial problem definition through data investigation, modelling, evaluation and communication of results.

• Work independently to understand the equipment or business problem, investigate the available data, establish ground truth, test potential solutions and evaluate 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.

Additional Responsibilities

• 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.

• 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.

Desirable Experience

• Experience developing predictive-maintenance, reliability, survivability or equipment-failure models.

• Experience working with IoT, connected-product or industrial telemetry data.

• Knowledge 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.

Candidate Profile

The successful candidate will be naturally curious, analytically rigorous and comfortable working in an environment where the problem and potential solution may not initially be fully defined. You should enjoy investigating complex datasets, understanding how physical equipment operates and translating analytical findings into solutions that deliver measurable engineering or customer value. You must be capable of working with a high level of autonomy while collaborating effectively with multidisciplinary product, data and engineering teams.

Contract Information

• Location: Galway

• Contract duration: Ten months

• Working arrangement: Full-time contract

Further details regarding the engagement structure will be discussed during the recruitment process.

Immediate interviews available for suitable candidates.

Note: By applying for this position, you may also be considered by Pale Blue Dot® Recruitment for other relevant opportunities.

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