Description

You will lead analytical efforts and manage the end-to-end machine learning lifecycle from development to production deployment.

Responsibilities

• Coordinate analytical plans and manage deliverables within an agile environment.
• Build and deploy predictive, prescriptive, and generative models using ML, DL, and LLM techniques.
• Implement features through the full ML lifecycle, including training, testing, production, and monitoring.
• Clean and model data from internal and external sources to support algorithmic development.
• Present technical findings and project status to business, technology, risk, and model governance stakeholders.

Required Skills

• 6+ years of industry experience in data science.
• 5+ years specializing in ML modeling, ranking, recommendations, or personalization systems.
• 5+ years designing scalable machine learning systems for training, inference, and monitoring.
• 3+ years of proficiency in Python, SQL, Spark, PySpark, and TensorFlow.
• Strong foundation in ML/DL/LLM algorithms, architectures, and training techniques.
• Experience deploying analytical solutions into production systems using the SDLC process.
• Ability to work both independently and collaboratively within a team.

Preferred Skills

• Experience with GenAI/LLM projects.
• Familiarity with distributed computing tools including Hadoop, Hive, Spark, and MySQL.
• Background in investment banking and risk management.
• Neo4j experience.

Key Skills

Education

Any Gradute