Senior Quantitative Analytics Specialist - Data Strat

About the Role

Role Responsibilities

• Use advanced statistical theories and techniques to quantify, analyze, and manage market-related opportunities and risks.
• Research data strategies and develop actionable insights for traders.
• Build, maintain, scale, and deploy end-to-end machine learning workflows and models.
• Design and implement Agentic AI workflows for automation and analytical frameworks.
• Own projects from requirements gathering and solution design through development and stakeholder delivery.
• Participate in analytical strategy, modeling, and forecasting discussions.
• Deliver high-quality software in an Agile environment and develop knowledge of data pipelines and ML application deployment.
• Support data strategy initiatives and comply with organizational policies, procedures, and risk requirements.

Required Qualifications

• At least 4 years of quantitative analytics experience, or equivalent experience, training, military experience, or education.
• A bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.

Desired Qualifications

• Strong statistical knowledge, including z-scores, correlation matrices, and related analytical techniques.
• Ability to prototype, design, and develop solutions for business challenges.
• Hands-on Python experience and the ability to contribute to data-driven solutions.
• Ability to lead process improvement initiatives and work effectively across teams and organizational levels.
• Experience with Python, Java, NumPy, Pandas, SciPy, Scikit-learn, visualization libraries, GitHub workflows, CI/CD platforms, and enterprise application technologies is valued.
• Experience with quantitative analytics or financial services, or willingness to learn these domains, is valued.

Technical Expectations

• Use Python and Java for analytical, software design, and development activities.
• Analyze and manipulate large datasets using NumPy, Pandas, SciPy, and Scikit-learn.
• Apply advanced Python object-oriented programming concepts, including classes, generators, decorators, exception handling, logging, and modular design.
• Perform data transformation and wrangling, including grouping, aggregation, pivoting, and handling missing or invalid values.
• Create and interpret visualizations with Matplotlib, Plotly, and Seaborn.
• Work with remote file servers, relational databases, NoSQL databases, and distributed systems.
• Use Jenkins, Docker, Kubernetes, React.js, Django, Flask, Streamlit, or Dash where applicable.
• Debug and support Java Spring Boot or similar enterprise applications and microservices.

Posting Information

• The posting end date is 27 Sep 2026, although the posting may close earlier due to applicant volume.

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