We are looking for a motivated Junior Data Scientist to support cutting-edge engineering projects by applying Data Science, Machine Learning, and advanced analytics techniques to real-world automotive engineering challenges.

The role involves working closely with engineering and IT teams across local and global locations to analyse complex datasets, develop predictive models, integrate AI/ML techniques into engineering workflows, and translate technical findings into actionable business and engineering insights. The ideal candidate should have a strong mathematical and statistical foundation, hands-on Python and Machine Learning experience, and the ability to communicate complex concepts clearly to both technical and non-technical stakeholders.

Key Responsibilities :

- Clean, analyse, process, and interpret large-scale datasets generated from engineering projects.

- Build, validate, and optimise statistical, analytical, and Machine Learning models to predict engineering performance metrics.

- Work closely with simulation engineers to integrate AI/ML techniques into simulation workflows beyond conventional surrogate modelling approaches.

- Identify patterns, correlations, trends, and anomalies within complex engineering datasets.

- Translate analytical findings into clear and effective data visualisations, reports, and presentations.

- Present insights and recommendations to engineers, project managers, and other stakeholders to support data-driven decision-making.

- Stay updated on emerging developments and trends across Data Science, Artificial Intelligence, and Machine Learning.

- Develop a conceptual understanding of new ML techniques and communicate their potential engineering applications clearly.

- Collaborate with international teams to understand their data requirements and jointly develop effective analytical solutions.

- Follow strong software engineering practices, including Clean Code principles.

Job Requirements :

- Masters degree in Computer Science, Data Science, Physics, Mathematics, Engineering, or a related discipline.

- Strong foundation in numerical methods, statistics, probability, and applied mathematics.

- Minimum 2 years of experience in Data Science, including relevant industry or academic experience.

- Strong proficiency in Python.

- Hands-on experience with data manipulation, analysis, and visualisation libraries such as :

1. Pandas

2. NumPy

3. Matplotlib

4. Seaborn

- Experience with one or more Machine Learning frameworks/libraries such as :

1. Scikit-learn

2. PyTorch

3. Keras

4. TensorFlow

- Foundational understanding of SQL and Object Relational Mapping (ORM).

- Strong understanding of and adherence to Clean Code principles.

- Strong analytical and problem-solving capabilities.

Preferred Qualifications :

- Prior internship, academic project, or professional experience within the automotive, electric vehicle, or manufacturing domain.

- Familiarity with automotive and vehicle data systems such as CAN bus and sensor data.

- Experience analysing vehicle or engineering sensor datasets.

- Exposure to simulation-driven development or Digital Twins.

- Knowledge of time-series analysis.

- Understanding of predictive maintenance algorithms and other AI/ML techniques used in engineering applications.

- Experience applying Machine Learning techniques to engineering simulations or physical systems will be an advantage.

Soft Skills :

- Strong analytical and structured problem-solving skills.

- Continuous-learning mindset with a passion for staying updated on developments in Data Science and Machine Learning.

- Proactive and collaborative approach to working within cross-functional teams.

- Ability to communicate technical concepts in a simple and understandable manner.

- Comfortable collaborating with global and multicultural teams.

- Fluent English communication skills.

What We Offer :

- Opportunity to work on cutting-edge AI and Machine Learning applications within a real-world engineering environment.

- Exposure to automotive engineering, simulation, predictive modelling, and advanced analytics use cases.

- Professional development opportunities with scope for continued career growth.

- Collaborative, inclusive, and innovation-focused work environment.

- Opportunity to work with a global team of technology, engineering, and mobility experts.

KEY SKILLS : Data Science, Machine Learning, Python, Predictive Modeling, Statistical Modeling, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, PyTorch, TensorFlow, Keras, SQL, ORM, Time Series Analysis, Predictive Maintenance, Digital Twin, Simulation, Automotive Data, CAN Bus, Sensor Data, Data Visualization