This role pays less than
92%
of similar roles. Most pay
$126,800–$196,337
— the shaded band above.
At the midpoint, this role pays about
$124k
versus about
$162k
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
176 open roles
on FindRole.
Listed pay typically runs
$120,000–$202,500
across 172 roles with salary data.
GCS, Data Scientist, AVP will join the team to support enterprise cybersecurity data science and analytics by transforming telemetry into actionable intelligence. The role involves developing statistical models, machine learning, graph analytics, NLP, and GenAI techniques to identify risk signals, detect anomalies, and improve security operations. You will analyze large structured, semi-structured, and time-series datasets using Python, SQL, PySpark, and Databricks while building reusable features, notebooks, and Power BI dashboards for technical and non-technical audiences. The position focuses on solving complex problems in threat detection, vulnerability prioritization, and risk scoring within a regulated environment. Key responsibilities include collaborating with cross-functional stakeholders to operationalize AI solutions and managing model lifecycle tasks like validation and explainability. You will work specifically with cybersecurity data sources such as endpoint telemetry, authentication logs, and SIEM/SOAR workflows to enhance decision-making.
What does a Data Scientist earn?
Median $162025 from 276 postings across 61 companies.
Develop machine learning, statistical, and AI models to identify risk signals and anomalies across cybersecurity datasets.
Analyze large-scale structured, semi-structured, graph, and time-series data using Python, SQL, PySpark, and Databricks.
Apply graph analytics and network science to uncover relationships between identities, assets, vulnerabilities, and threat indicators.
Utilize NLP and GenAI techniques to summarize, classify, and enrich security logs, tickets, and investigation notes.
Build reusable analytical datasets, features, and models that scale across enterprise security use cases.
Create Power BI dashboards to communicate model outputs, cyber trends, and risk insights to technical and non-technical audiences.
Ensure responsible model development by managing validation, performance monitoring, explainability, and documentation in a regulated environment.
Evaluate emerging technologies in ML, graph analytics, and cloud data to improve cybersecurity outcomes.
What we're looking for
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Cybersecurity, Information Systems, or equivalent practical experience.
5-8 years of professional experience in data science, analytics, machine learning, data engineering, or related technical roles.
2-4 years of experience applying data science or machine learning to cybersecurity, risk, fraud, infrastructure, or identity datasets.
Proficiency in Python and SQL for analytical modeling, statistical evaluation, and data manipulation.
Experience using PySpark and Databricks to process and model large-scale datasets.
Ability to create actionable dashboards and visualizations using Power BI or similar business intelligence tools.
Working knowledge of AWS data services and familiarity with SIEM/SOAR platforms and security workflows.
Expertise in advanced analytics including graph analytics, NLP, GenAI, anomaly detection, and classification.
Python
PySpark
SQL
Databricks
ETL
API
Machine Learning
Natural Language Processing
Qlik
Advana
Maven
Data Governance
Cybersecurity
Data Engineering
Analytics