Generative AI Data Scientist - Multi-Agent RAG (NYC Onsite)

DataJobs; New York (NY); On-site; USD 148,000 - 169,000; Full time

Benefits offered by this job

Performance-based incentives

Comprehensive benefits

Job summary

DataJobs is seeking a Senior Associate in New York, onsite, to deliver enterprise-grade Generative AI solutions within the Commercial Bank Applied AI group. You will collaborate with data scientists, ML engineers, and product managers to deploy Multi-Agent and RAG pipelines at scale.

You will work with Python, PyTorch, LangChain, AWS, Spark, and Vector Databases across the full model lifecycle—context engineering, fine-tuning, evaluation, validation, and deployment—while translating technical

Qualifications

• Bachelor’s degree in a quantitative field plus 2 years of analytics experience.
• Master’s degree in a quantitative field or MBA with quantitative concentration.
• At least 2 years of experience with Python, Scala, or R.
• At least 2 years of experience with machine learning.
• At least 2 years of experience with SQL.
• At least 1 year of experience in AI, Information Retrieval, Deep Learning, and NLP.
• Master’s or PhD in STEM fields.

Responsibilities

• Collaborate with data scientists, ML engineers, and product managers to deliver Generative AI solutions.
• Build Multi-Agent systems and advanced RAG pipelines across large data sets.
• Develop Generative AI models and pipelines end-to-end: context engineering, fine-tuning, evaluation, validation, deployment.
• Translate technical work into clear business goals.

Skills

Python/Scala/R

ML/AI

SQL

Education

Bachelor’s degree in a quantitative field

Master’s degree in quantitative field or MBA with quantitative concentration

STEM Master’s or PhD

Tools

Python

PyTorch

LangChain

AWS

Spark

Vector Databases

Job description

DataJobs is seeking a Senior Associate in New York, onsite, to deliver enterprise-grade Generative AI solutions within the Commercial Bank Applied AI group. You will collaborate with data scientists, ML engineers, and product managers to deploy Multi-Agent and RAG pipelines at scale.

You will work with Python, PyTorch, LangChain, AWS, Spark, and Vector Databases across the full model lifecycle—context engineering, fine-tuning, evaluation, validation, and deployment—while translating technical