Data Scientist: Manufacturing Analytics & ML

EVera Recruitment; Coventry; On-site; GBP 52,000 - 70,000; Full time

Job summary

EVera Recruitment is seeking a Data Scientist to transform manufacturing and product data into actionable insights that enhance quality, performance and decision-making. You will work with engineering, manufacturing and digital teams to apply analytics, statistics and ML to engineering challenges.

You will analyse datasets, develop models and dashboards, and present findings to both technical and non-technical stakeholders to drive improvements in product and manufacturing performance.

Qualifications

• MSc, MEng or equivalent in Engineering, Science or Data discipline.
• Experience analysing manufacturing, operational or quality datasets.
• Strong programming skills in Python or Java.
• Experience with SQL databases and data visualization tools.
• Knowledge of statistics, data modelling and machine learning.
• Strong communication and problem-solving skills.

Responsibilities

• Analyse manufacturing, quality and product performance data to identify trends and improvement opportunities.
• Develop analytical models, dashboards and reporting tools.
• Apply statistical and machine learning techniques to support engineering decisions.
• Define data and reporting requirements with engineering and digital teams.
• Support simulation and modelling activities using real-world data.
• Present findings and recommendations to technical and non-technical stakeholders.

Skills

Python

Java

Data analysis

Machine learning

Data visualization

Problem-solving

Communication

Education

MSc / MEng or equivalent

Tools

SQL databases

Data viz tools

Job description

EVera Recruitment is seeking a Data Scientist to transform manufacturing and product data into actionable insights that enhance quality, performance and decision-making. You will work with engineering, manufacturing and digital teams to apply analytics, statistics and ML to engineering challenges.

You will analyse datasets, develop models and dashboards, and present findings to both technical and non-technical stakeholders to drive improvements in product and manufacturing performance.