Automotive Data Scientist (ML Focus) - Hybrid

Placements24; Soweto; Hybrid; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Hybrid work model

Competitive salary

Career growth

Health benefits

Job summary

Placements24 in Soweto is seeking an Automotive Data Scientist with a strong ML focus to drive analysis across sensor, telematics, and manufacturing data. You will develop models for predictive maintenance, anomaly detection, and performance optimization while collaborating with engineers and product teams.

The role combines on-site collaboration with remote flexibility in a hybrid work environment and emphasizes data governance, model deployment, and stakeholder communication.

Qualifications

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field.
• Minimum of 5 years of experience as a Data Scientist or Machine Learning Engineer.
• Proficiency in Python or R.
• Strong experience with ML libraries and frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with large datasets and databases (SQL, NoSQL).
• Familiarity with data visualization tools (Tableau, Power BI, Matplotlib).
• Knowledge of cloud platforms (AWS, Azure, GCP) is a plus.

Responsibilities

• Collect, clean, and transform large volumes of automotive data for analysis.
• Develop, train, and evaluate ML models for predictive maintenance, anomaly detection, and performance optimization.
• Apply statistical methods to identify trends and insights within automotive data.
• Design and implement experiments to test hypotheses and validate model performance.
• Visualize data and model results for stakeholders.
• Collaborate with automotive engineers and product teams to understand data needs.

Skills

Python

R

Machine learning

SQL

Education

Master's or PhD in Data Science/Statistics/CS/Math

Tools

TensorFlow

PyTorch

Scikit-learn

Tableau

Power BI

Job description

Placements24 in Soweto is seeking an Automotive Data Scientist with a strong ML focus to drive analysis across sensor, telematics, and manufacturing data. You will develop models for predictive maintenance, anomaly detection, and performance optimization while collaborating with engineers and product teams.

The role combines on-site collaboration with remote flexibility in a hybrid work environment and emphasizes data governance, model deployment, and stakeholder communication.