Description

You will design, develop, and optimize machine learning models and data pipelines using Azure Databricks and Python.

This role is hybrid.

Responsibilities

• Design and implement machine learning models for forecasting, classification, and clustering.
• Perform feature engineering, model validation, and performance tuning using Python and PySpark.
• Prepare structured and unstructured data, ensuring quality through cleansing and validation scripts.
• Conduct deep-dive analyses to identify trends and communicate findings to technical and non-technical stakeholders.
• Collaborate with data engineering teams to maintain efficient data pipelines and governance standards.

Required Skills

• 7+ years of experience in data science and machine learning engineering.
• Proficiency in Python, PySpark, and Pandas for data science workloads.
• Strong SQL knowledge and experience with relational databases.
• Experience with Azure Databricks and Google Cloud Platform.
• Knowledge of ML Ops, MLOps practices, and large language models (GenAI).
• Familiarity with Natural Language Processing (NLP) and A/B testing.
• Experience with data visualization tools such as Power BI and DAX queries.
• Solid understanding of data structures and algorithms.

Preferred Skills

• Databricks Certified Data Engineer Associate certification.
• Experience with statistical methods and experimental design.

Key Skills

Education

Bachelor's or Master's degrees