Description
You will apply advanced machine learning algorithms to solve classification problems within the automotive and logistics domains.
Responsibilities
- Implement classification algorithms including Random Forest, LightGBM, and XGBoost.
- Develop propensity models using Python.
- Write complex SQL queries utilizing window functions like Rank and Lead.
- Explain model outputs and statistical inferences to stakeholders.
- Apply Bayesian Statistics or Sales Incentive modeling to business problems.
Required Skills
- 7 to 9 years of experience in Data Science.
- Hands-on expertise with Random Forest, LightGBM, and XGBoost.
- Proficiency in Python programming.
- Advanced SQL skills, specifically using window functions.
- Experience with classification problem solving.
- Domain knowledge in Automotive Industry and After Sales & Service Management Logistics.
- Any Graduate degree.
Preferred Skills
- Experience with Databricks and AWS services including Athena, SageMaker, and S3.
- Familiarity with Jupyter Notebooks in SageMaker Studio.