Description

You will design, build, and deploy machine learning models and data pipelines using Azure Databricks and Google Cloud.

This role is hybrid.

Responsibilities

• Design, train, and optimize machine learning models for forecasting, classification, and clustering.
• Implement ML Ops practices, including model validation, performance tuning, and deployment.
• Prepare structured and unstructured data using PySpark and Python for advanced analytics.
• Analyze complex datasets to uncover patterns, perform feature engineering, and drive actionable insights.
• Collaborate with data engineers to maintain efficient data pipelines and resolve dashboard errors.

Required Skills

• 7+ years of experience in data science and machine learning engineering.
• Proficiency in PySpark and Pandas for data science workloads.
• Strong SQL knowledge and experience with relational databases.
• Experience with Azure Databricks and Google Cloud infrastructure.
• Familiarity with scikit-learn, NumPy, and modern data science libraries.
• Experience with Machine Learning Operations (MLOps).
• Experience with GenAI, Large Language Models (LLMs), and Natural Language Processing (NLP).
• Proficiency with data visualization tools, specifically Power BI and DAX queries.

Preferred Skills

• Data Structures and Algorithms knowledge.
• Experience with A/B Testing and statistical methods.

Key Skills

Education

Bachelor's or Master's degrees