Senior Data Scientist, Agentic AI / Graph / LLM Science

State Street

Quick summary

Work type
On-site
Location
Quincy, MA
Salary
$120,000–$202,500 / yr
Posted
3 days ago
Closes
Jul 31, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $196k
This role $161k
$107k most similar roles pay here $243k

This role pays less than 77% of similar roles. Most pay $162,000–$229,400 — the shaded band above. At the midpoint, this role pays about $161k 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 136 open roles on FindRole.

Listed pay typically runs $120,000–$190,000 across 134 roles with salary data.

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At a glance

TL;DR · Senior Data Scientist, Agentic AI / Graph / LLM Science

We are seeking a Data Scientist to join our AI/ML science team at the Agentic AI platform buildout. This senior-level role involves applied research and product-oriented data science tasks, including designing domain-specific LLM solutions, building evaluation frameworks, and operationalizing fine-tuning for business use cases. The ideal candidate will own specific problem statements, conduct robust evaluations of foundational models, develop knowledge graphs, and optimize inference engines for scalable serving in production environments. Key skills include hands-on experience with large language models (LLMs) at scale, proficiency in Python and ML libraries such as PyTorch and TensorFlow, and familiarity with cloud platforms like AWS or GCP. Strong understanding of graph databases and MLOps practices is essential, with prior work on agentic AI being a significant advantage.

What you'll do

  • Own and deliver value for business unit-specific problem statements using agentic AI workflows.
  • Conduct LLM research, fine-tuning, and prompt optimization with robust data governance.
  • Develop evaluation frameworks and taxonomies to assess model performance rigorously.
  • Build knowledge graphs and embeddings for semantic search and reasoning capabilities.
  • Design inference engines for scalable, low-latency serving of tuned models in production.

What we're looking for

  • 5+ 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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