This role pays more than
59%
of similar roles. Most pay
$174,600–$281,250
— the shaded band above.
At the midpoint, this role pays about
$238k
versus about
$228k
for comparable roles.
Based on 240 similar postings.
Employer
About MSCI
MSCI is a US-based provider of investment decision support tools, including equity indexes, portfolio risk and performance analytics, and ESG research used by institutional investors worldwide.
MSCI currently has
14 open roles
on FindRole.
Listed pay typically runs
$195,000–$250,000
across 14 roles with salary data.
The Distinguished Principal Engineer - AI Science is an individual contributor role within the core product teams, focusing on the intersection of advanced data science, machine learning, and product engineering. You will build production-grade machine learning models, scale AI pipelines, and embed generative AI agents to solve complex financial workflows for global clients. Key responsibilities include developing algorithms using Natural Language Processing, Causal-ML, Deep Learning, Reinforcement Learning, and LLMs, while establishing evaluation methodologies for accuracy, explainability, and fairness. You will architect reusable pipeline infrastructure and lead technical roadmaps for specific product areas. The role requires expert proficiency in optimization paradigms and experience with Python, Scala, Java, or R, alongside strong SQL capabilities. This position addresses the challenge of transforming research prototypes into stable production services within a high-stakes financial platform environment.
What does a Engineer earn in California?
Median $208000 from 94 postings across 22 companies.
Develop advanced machine learning models using NLP, Causal-ML, Deep Learning, and Generative AI to solve financial problems.
Design and build Minimum Viable Products (MVPs) to test new AI-driven experiences in collaboration with product teams.
Lead the technical roadmap and architecture design for data science solutions within specific product areas.
Build and standardize evaluation methodologies to ensure model accuracy, explainability, and responsible AI practices.
Architect robust, end-to-end reusable pipelines to transition research prototypes into stable production-level services.
Translate complex algorithmic logic into actionable business insights for senior leadership and non-technical stakeholders.
Integrate emerging academic and industry AI trends into the company's core products.
Provide technical mentorship to junior engineers to foster a culture of technical excellence.
What we're looking for
Bachelor’s, Master’s, or Ph.D. in a highly quantitative discipline such as Computer Science, Statistics, Mathematics, Operations Research, or Economics.
10+ years of cumulative industry experience in a dedicated data science or machine learning capacity.
3+ years of experience acting as a technical lead steering data science initiatives or managing mission-critical ML workflows.
Expert-level proficiency in optimization paradigms and foundational machine learning frameworks.
Deep hands-on coding experience in big data environments using Python, Scala, Java, or R.
Strong SQL capabilities for data manipulation and analysis.
Proficiency in advanced techniques including NLP, Causal-ML, Deep Learning, Reinforcement Learning, and Generative AI.
Ability to translate complex algorithmic logic into business-focused insights for non-technical stakeholders.
Machine Learning
NLP
Deep Learning
Causal-ML
Bayesian Learning
Reinforcement Learning
Python
Scala
Java
R
ETL
Explainable AI
Data Mining
Scrum
Git
Statistics
Optimization
Data Science