Lead Quantitative Analytics Specialist

In this role, you will:

• Lead and contribute to moderately complex quantitative modeling and analytical initiatives, including model development, implementation, documentation, testing, and validation

• Apply statistical methods and quantitative analysis to monitor markets and assess credit and operational risk within a defined scope

• Analyze data and market developments to support short- and long-term business objectives and defined strategic initiatives

• Apply knowledge of stochastic methods, structured securities, and spread analysis to evaluate financial instruments, market behavior, and model results

• Review and assess quantitative models from technical, model-risk, audit, and market perspectives, identifying issues and recommending appropriate enhancements

• Define the structure and scope of assigned model reviews in accordance with established standards, policies, and control requirements

• Exercise independent judgment to develop, document, and evaluate analytical models that support product, marketing, risk, and business decisions

• Collaborate and consult with internal partners, model stakeholders, auditors, and regulatory-facing teams to address moderately complex model and analytical matters

• Present analytical findings, model limitations, risks, and recommendations clearly to technical and business stakeholders

Required Qualifications:

• 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

• Experience in the field of data science and analytics with hands on working knowledge in related tools and technologies.

• Deep working knowledge of machine learning and deep learning, including model selection, training dynamics, overfitting, and evaluation tradeoffs.

• Practical mastery of prompt engineering and LLM behavior control, including structured prompting, chain-of-thought, robustness, and security considerations.

• Ability to design and optimize Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, chunking, and reranking techniques.

• Experience with model evaluation, monitoring, and Responsible AI, including bias, hallucination mitigation, governance, and human-in-the-loop validation.

• Strong MLOps/LLMOps capabilities, covering model lifecycle management, experiment tracking, deployment, cost control, and latency optimization.

• Ability to develop, analyze and optimize performance of Gen AI, Agentic AI solutions.

• Proficiency in Python-based data science and software engineering, with experience integrating GenAI into scalable, production-grade system

• Provide exploratory data analysis using Python/R/SAS / SQL

• Experience with Databases like oracle, Teradata, SQL server

• Advance Excel skills

• Data integration and clean up data for the usage

• Strong oral and written communication and consultative skills

• Proactively seek opportunities to increase the value of analysis

• Ensure partner transparency throughout the life of the project

• Ensure that analyses are delivered on time, while surpassing partner expectations

• Present findings to multiple levels of management

• Consult with partners to define issues/information needs

• Find opportunities in the data and able to communicate to the partners

• Trend Analysis, forecasting and pattern recognition

• Data mining and Insights