EY - Data Scientist/Machine Learning Engineer

- Strong proficiency in Python, especially in analytical contexts, is essential.

- Fundamental understanding of data visualization and data imputation techniques.

- Familiarity with various machine learning models and functions, prioritizing supervised learning. Experience with Forecasting (Time series), Optimization techniques, etc.

- Understanding of linear regression, what's the input data and error debugging techniques, is key.

- Experience in the CPG domain is preferred but not mandatory.

- Strong grasp of supervised learning, with some knowledge of unsupervised learning, such as K-means clustering.

- Working experience with end-to-end ML Life Cycle

- Good knowledge of why a particular ML technique is being used in the case and not just how

- Fluent in Python (must have) and SQL (good to have)

- Some working experience in Model Deployment and Cloud Services

- Familiarity with software development practices, version control, and agile methodologies. (good to have)

Notice period: Max 30 days preferred