Direct employment by the client – Company employee from Day 1.

A leading financial company is looking for an experienced and innovative Data Scientist to join their core data team. In this role, the selected candidate will design, develop, and deploy end-to-end Machine Learning and Generative AI solutions, driving impact from initial research to production monitoring within a complex, large-scale financial ecosystem.

Key Responsibilities

• End-to-End ML Solutions: Lead data solutions from research, data collection, and mapping to EDA, feature engineering, descriptive statistics, and preliminary analyses. Select algorithms and train models using advanced ML and GenAI methodologies.
• GenAI & LLM Optimization: Perform fine-tuning for LLMs, embeddings, vector stores, and RAG architectures.
• Production Deployment: Deploy models into production in collaboration with ML Engineering, DevOps, and core system developers.
• Monitoring & Maintenance: Monitor model performance in production, detect model drift, and orchestrate retraining as needed.
• Business Collaboration: Interface with business stakeholders to present project outcomes, insights, and data-driven value.
• Methodological Leadership: Drive initiatives to enhance workflows, best practices, and ML/AI methodologies across the unit and organization.

Requirements

• Education: B.Sc. in Engineering, Computer Science, Mathematics, Statistics, or Data Science – Must.
• Experience: 2+ years of hands-on experience as a Data Scientist – Must.
• Python Mastery: Strong proficiency in Python and leading ML libraries – Must.
• SQL: Advanced proficiency in SQL – Must.
• GenAI Expertise: Practical experience with Generative AI and LLM technologies – A highly significant advantage.