Description

Key Skills: Machine Learning, SQL, Docker, Python, Forecasting, PowerBI, MatPlotLib, Visualization, Tableau

Roles and Responsibilities:

• Design, develop, and deploy machine learning models for predictive pricing/valuation and vehicle condition/wear prediction using automotive datasets.
• Build and maintain end-to-end ML pipelines in Python, including data preprocessing, feature engineering, and model evaluation.
• Containerize and deploy ML services using Docker and production APIs where applicable.
• Monitor model performance in production, retrain/optimize models, and improve reliability over time.
• Create dashboards and visualizations to communicate insights and support pricing and valuation decisions.

Skills Required:

• 3-5 years of relevant experience in data science and machine learning.
• Machine learning model development and deployment experience.
• Python for end-to-end ML pipeline development and model implementation.
• SQL for working with structured automotive data and building reliable datasets for modeling.
• Docker for packaging and deploying ML components in production environments.

Good to Have:

• Matplotlib and visualization experience for analysis and reporting.
• Tableau and/or PowerBI for dashboarding and stakeholder reporting.
• Forecasting experience for time-series or demand/pricing related use cases.

Education: Bachelor's degree in Computer Science, Data Science, Statistics, or related field

Key Skills

Education

Any Graduate