Senior GenAI Data Scientist

Client

Our client is a leading Fortune 500 financial technology company that provides comprehensive payment solutions and financial services across multiple continents. They process billions of transactions annually and serve millions of customers worldwide.

You'll collaborate with a world-class team of senior data scientists, ML engineers, and technology consultants from leading organizations in the fintech and cloud computing space. This diverse group brings together deep technical expertise, industry knowledge, and proven experience delivering mission-critical solutions at enterprise scale.

Position overview

We are seeking an experienced Senior Data Scientist with deep expertise in Generative AI implementations. This role is designed for seasoned data science professionals who have successfully transitioned their expertise into production GenAI environments - not for those simply exploring AI technologies.

Technology stack

AWS Bedrock, SageMaker, and comprehensive AI/ML service ecosystem
Vector databases and advanced RAG architectures
Enterprise-scale data processing and real-time model deployment systems
Automated CI/CD pipelines specifically designed for ML workflows

Responsibilities

• Design and implement data architectures for GenAI solutions across structured, semi-structured, and unstructured data sources
• Extract, prepare, and optimize data for consumption into AI platforms from data lakes and direct model ingestion
• Structure diverse data sources for proper ingestion into AI workflows and model training
• Develop and manage automated data streams and pipeline orchestration
• Collaborate with MLOps engineers to ensure seamless data flow for model training and inference
• Implement data quality monitoring and validation frameworks for GenAI applications
• Design feature engineering strategies specifically for Foundation Models and LLM implementations
• Scale proof-of-concepts to production-ready, enterprise-grade data solutions

Requirements

• Hands-on experience with diverse data sources (structured, semi-structured, unstructured) for AI platform integration
• Proven ability to extract, prepare, and structure data for consumption into AI platforms from data lakes or direct model ingestion
• Experience structuring various data sources for proper ingestion into AI workflows and Foundation Model training
• Advanced knowledge of automated data stream management and pipeline orchestration for AI/ML workloads
• Demonstrated experience building scalable data infrastructure supporting GenAI applications in production environments
• Strong background in AWS data services (S3, Glue, Kinesis, etc.) and integration with AI/ML platforms
• Advanced Python, SQL, and experience with big data technologies (Spark, Kafka, etc.)
• Proven track record of transitioning POCs to production-ready, enterprise-scale data solutions
• 5+ years data science experience with 2+ years dedicated GenAI data engineering and preparation experience
• Availability during US Eastern Time (ET) business hours to collaborate with onsite team

Nice to have

• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, or related technical field (Master's preferred)
• AWS certifications (Data Analytics, Machine Learning Specialty, etc.)
• Experience with financial services or payment processing data systems
• Knowledge of data governance and compliance frameworks in regulated industries