Senior Associate, Data Scientist - Applied AI

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

This role sits within the Commercial Bank Applied AI organization, focused on bringing Generative AI into core business processes. You will work as a Senior Associate in an environment that builds enterprise-grade Multi-Agent and RAG systems, taking solutions from development through deployment while collaborating closely with cross-functional partners.

Based in New York, NY, this position is onsite and offers an annual salary range of USD 148,000 to 168,900. The minimum experience requirement is 2 years.

What you’ll do

• Collaborate with a cross-functional team of data scientists, machine learning engineers, and product managers to deliver Generative AI solutions for customers.
• Use a broad technology stack including Python, PyTorch, LangChain, AWS, Spark, and Vector Databases to build Multi-Agent systems and advanced RAG pipelines over large volumes of numeric and textual data.
• Develop Generative AI models and pipelines across the full lifecycle, including context engineering, fine-tuning, evaluation, validation, and deployment.
• Apply interpersonal skills to translate technical work into clear business goals.

What you’ll need

• Bachelor’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics.
• OR a Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field), or an MBA with a 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 degree in a STEM field (Science, Technology, Engineering, or Mathematics), or a PhD in a STEM field.

Tools and technologies

• Python, PyTorch, LangChain, AWS, Spark, Vector Databases
• Multi-Agent Systems, Advanced RAG
• Context Engineering, Tool-Calling Frameworks
• Fine-tuning, evaluation, validation, deployment
• SQL

Benefits

• Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
• A comprehensive, competitive, and inclusive package of health, financial, and other benefits to support total well-being.

Team focus

The Commercial Bank Applied AI team focuses on embedding Generative AI directly into core business processes. The work emphasizes enterprise-grade architectures using advanced techniques such as Multi-Agent Systems, Advanced RAG, Context Engineering, and Tool-Calling Frameworks. The team values candidates who are passionate about practical applications of Generative AI and bring hands-on experience in machine learning and AI developed through professional work or rigorous academic research.

Ideal candidate profile

• Innovative: researches and evaluates emerging technologies.
• Creative: defines approaches to big, undefined problems.
• Technical: comfortable with open-source languages and focused on building data science solutions using open-source tools and cloud computing platforms.
• Statistically-minded: builds, validates, and backtests models; understands and interprets metrics such as confusion matrices and ROC curves; has experience with clustering, classification, sentiment analysis, time series, and deep learning.