Director of Financial Engineering & Execution Strategy

Soteria Reinsurance Ltd.; Boston, Northern (MA, KY); Hybrid; USD 170,000 - 185,000; Full time

Job summary

Soteria Reinsurance Ltd. seeks a Director of Financial Engineering to lead research and development of cost-aware execution strategies for US equity markets.

The role involves building models, performance metrics, and analytical frameworks to improve execution quality and scalability across client objectives. You will design and optimize algorithms, measure post-trade performance, and apply ML methods using KDB/Q and Python within an AWS-based cloud environment.

Qualifications

• Bachelor's degree in CS/Engineering/IT/Info Systems/FinTech or related field; foreign degrees accepted.
• Six years of experience as Director, Financial Engineering or similar; transaction cost analysis in US markets with KDB/Q and Python.
• Expertise in ML algorithms, quantitative forecasting, and DeFi analysis using Python and KDB/Q.

Responsibilities

• Lead research on experimental design and analytical controls to drive platform improvements.
• Define performance frameworks for evaluating systematic trading platforms.
• Analyze trading and execution data to reduce costs and improve customer outcomes.
• Develop methods to assess market conditions' impact on platform performance.
• Translate research into scalable improvements via Agile processes.
• Evaluate execution quality and post-trade trends; suggest methodological changes.

Skills

Python

KDB/Q

ML algorithms

Quant forecasting

Market analysis

Education

Bachelor's degree in a related field

Six years of director-level experience

Tools

KDB/Q

AWS

scikit-learn

Vowpal Wabbit

Job description

Soteria Reinsurance Ltd. seeks a Director of Financial Engineering to lead research and development of cost-aware execution strategies for US equity markets.

The role involves building models, performance metrics, and analytical frameworks to improve execution quality and scalability across client objectives. You will design and optimize algorithms, measure post-trade performance, and apply ML methods using KDB/Q and Python within an AWS-based cloud environment.