Description

You will lead complex data science initiatives from inception through to production deployment.

Responsibilities

• Develop and deploy machine learning models and statistical analyses into production environments.
• Orchestrate end-to-end data science workflows using cloud analytics platforms like Databricks.
• Implement MLOps practices, including model versioning, CI/CD for ML, and performance monitoring.
• Collaborate with data engineering teams to design and optimize data pipelines leveraging Lakehouse or data warehouse architectures.
• Mentor junior data scientists through code reviews and structured skill development.

Required Skills

• 5+ years of professional experience leading data science initiatives.
• 3+ years experience with Databricks or similar cloud-based analytics platforms.
• 3+ years applying advanced predictive modeling (regression, classification, NLP, forecasting).
• 2+ years experience implementing MLOps practices (MLflow, CI/CD for ML).
• 2+ years experience designing data pipelines with Snowflake or SQL-based platforms.
• 2+ years proficiency in Python and SQL with databases like SQL Server, Oracle, or PostgreSQL.
• 2+ years experience mentoring or supervising junior data scientists.
• 1+ year experience operationalizing analytics within enterprise governance frameworks.
• Possession of a Master's degree in Data Science, Statistics, or Computer Science.

Key Skills

Education

Master's degree