Controls Room Quant Analytics, Senior Associate

The Controls Room Team is looking for a technically skilled and driven analytics professional to join our high-performing organization. This is a high-impact opportunity to support Control Management with data automation, predictive analytics, and AI-enabled tools. We are seeking someone who thrives in complexity, builds scalable Python-based solutions, and contributes to the team’s transformation toward proactive risk insight. You will join an agile and collaborative team working across multiple disciplines and high-visibility projects. If you’re passionate about using advanced analytics to solve meaningful challenges, we’d love to have you on the team.

Job Summary:

As a Quant Analytics, Senior Associate within the Control Management Controls Room team, you will help design and implement scalable data tools and LLM solutions that power regulatory risk assessments. You’ll work closely with control managers, SMEs, and technologists to automate workflows, structure complex data, and support predictive modeling efforts. This is a dynamic, technical role with high visibility, and a strong focus on forward-looking analytics and responsible AI adoption. Youll have the opportunity to drive innovation, strengthen enterprise reporting, and mentor others on automation and backend development practices.

Job Responsibilities:

• Build and maintain Python-based data pipelines and backend tools to support regulatory-driven risk assessments
• Develop and operationalize LLM-powered analytics solutions, including prompt workflows and validation methods
• Design predictive analytics models to support proactive risk identification and control effectiveness evaluation
• Integrate data from APIs, enterprise platforms, and structured/unstructured sources to enable scalable automation
• Partner with stakeholders to gather requirements and develop fit-for-purpose analytics tools
• Translate unstructured content into structured data formats for downstream analytics and LLM ingestion
  
• Conduct exploratory data analysis to identify trends and inform regulatory risk insights
• Support model refinement efforts aligned to firmwide AI/ML policies and governance standards
• Participate in Agile ceremonies and working groups to align priorities, deliverables, and timelines
• Provide mentorship and technical support on Python, automation, and data engineering practices
• Collaborate cross-functionally to design tools that enhance transparency and decision-making

Required Qualifications, Capabilities and Skills:

• 5+ years of experience in data analytics, backend Python development, or data engineering, and a Bachelor’s degree is required, preferably in a quantitative or technical field (e.g., Computer Science, Statistics, Engineering)
• Advanced proficiency in Python (pandas, numpy, requests, json), with experience writing modular scripts and implementing unit tests using frameworks like pytest
• Strong experience with RESTful APIs and handling data ingestion pipelines
• Experience supporting LLM/NLP-based tools and prompt workflows
• Proficiency in SQL and knowledge of relational data structures
• Familiarity with Agile tools and processes (e.g., Git, JIRA, Bitbucket, Github)

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  Strong communication skills with the ability to present to both technical and non-technical audiences
• Experience working in high-complexity environments across multiple business and technology teams
• Ability to translate business needs into technical designs and solutions
• Track record of delivering high-impact, scalable data tools
• Strong attention to detail, critical thinking, and problem-solving skills

Preferred Qualifications, Capabilities and Skills:

• Experience in control testing, regulatory risk, or compliance-focused analytics
• Exposure to frameworks like FastAPI, Flask, or LangChain
• Experience with Python data visualization libraries (e.g., Plotly, Seaborn, Matplotlib)
• Familiarity with Tableau or Power BI for stakeholder-focused dashboards
• Understanding of AI governance, hallucination mitigation, and LLM safety practices
• Knowledge of metadata management, data modeling, and governance standards
• Experience working with enterprise platforms and cross-functional stakeholders