Data Scientist – Agentic AI / Graph/ LLM Science , Assistant Vice President

State Street

Quick summary

Work type
On-site
Location
Quincy, MA
Salary
$90,000–$157,500 / yr
Posted
25 days ago
Closes
Jul 31, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $196k
This role $124k
$73k most similar roles pay here $252k

This role pays less than 98% of similar roles. Most pay $157,200–$234,362 — the shaded band above. At the midpoint, this role pays about $124k versus about $196k for comparable roles.

Based on 240 similar postings.

Employer

About State Street

State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody

State Street currently has 63 open roles on FindRole.

Listed pay typically runs $120,000–$177,500 across 62 roles with salary data.

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View all roles at State Street

At a glance

TL;DR · Data Scientist – Agentic AI / Graph/ LLM Science , Assistant Vice President

We are seeking a Data Scientist to join our AI/ML science team as part of the Agentic AI platform buildout. This role involves applied research and product-oriented data science, focusing on designing and validating domain-specific LLM solutions, building evaluation frameworks, and operationalizing fine-tuning for business use cases. The candidate will work closely with engineering teams to deploy scalable AI solutions in production environments, conduct experiments to benchmark model performance, and develop knowledge graphs and embeddings for semantic search. Required skills include a degree in Computer Science or related field, 3+ years of experience in applied machine learning or NLP, hands-on experience with LLMs at scale, proficiency in Python and ML libraries like PyTorch and TensorFlow, and familiarity with cloud platforms and MLOps practices. Prior work on agentic AI is highly desirable.

What you'll do

  • Design and validate domain-specific LLM solutions for business use cases.
  • Develop evaluation frameworks and taxonomies to assess model performance.
  • Fine-tune large language models with robust data curation and governance.
  • Build scalable inference engines for low-latency serving of tuned models.
  • Maintain knowledge graphs and embeddings for semantic search and reasoning.
  • Conduct experiments to benchmark model performance and ensure robustness.

What we're looking for

  • 3+ years of experience in applied machine learning or NLP.
  • Hands-on experience with large language models (LLMs) and natural language processing at production scale.
  • Strong understanding of graph databases and knowledge graph construction.
  • Proficiency in Python and major ML libraries like PyTorch, TensorFlow, and Scikit-learn.
  • Familiarity with cloud platforms and MLOps practices for scalable AI solutions.

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