Technical Manager, Strategy Research Analytics

Voleon is a technology company applying state-of-the-art machine learning to real-world financial problems. With over a decade of leadership in our industry, we've built a multibillion-dollar asset management firm and continue to drive ambitious innovations. Voleon is a technology company applying state-of-the-art machine learning to real-world financial problems. With over a decade of leadership in our industry, we’ve built a multibillion-dollar asset management firm and continue to drive ambitious innovations. As Technical Manager, Strategy Research Analytics, you will lead a high-impact team responsible for maintaining and evolving Voleon’s core analytics pipelines and data models — ensuring reliability today while building toward a world-class analytics platform that accelerates our core strategy research velocity and insight generation. Operating at the intersection of research, engineering, and data infrastructure, you’ll translate the needs of researchers and data scientists into robust, scalable, and reproducible analytics systems. You’ll collaborate with leaders across Research, Engineering, ProdOps, and Data Infrastructure to define a clear roadmap for analytics enablement, drive operational excellence, and empower data scientists to focus on high‑value research analysis. You’ll drive team execution, clarify ownership boundaries, and ensure visibility and accountability for a growing, mission-critical capability within the research organization. Your Team The Research Analytics team sits within Research Engineering and works closely with Data Scientists and Researchers across all of Voleon's core strategies. We look for brilliant people with a passion for solving problems through innovation and engineering fundamentals. You’ll work in a collaborative environment that encourages creative thinking and efficient implementation. You’ll work alongside experienced engineers recruited from leading technology companies and selected from the sharpest minds at university programs. The team’s mission is to: Deliver reliable, monitored, and observable analytics pipelines that underpin our most critical research insights. Design and maintain a consistent, queryable analytics data model that supports scalable, reproducible analysis in a distributed compute environment. Enable modern analytical tooling (Presto, Spark, Dask, Polars) to improve accessibility and speed of research workflows. Promote data transparency, discoverability, and documentation as first-class engineering objectives. Responsibilities

Recruit, mentor, and develop a diverse team of engineers and data specialists, starting with a small core team that will grow to meet the evolving needs of the organization. Build capacity not only to maintain existing pipelines but also to develop and execute on a forward-looking vision for a scalable, world-class analytics platform

Work with existing stakeholders to define and communicate a long-term strategy for analytics infrastructure and enablement, building a vision that solves real-world problems for our data scientists and extends toward a standardized, industry-class analytics platform

Lead team execution in a complex, fast-paced research environment, reducing friction and optimizing workflows

Influence laterally across engineering and research teams to align roadmaps, shape priorities, and drive shared goals

Ensure robust communication of team progress, creating transparency and credibility with senior stakeholders

Oversee consistent, well-documented, and queryable data models that power research today, and extend these frameworks toward the broader vision of a unified analytics platform

Requirements

Bachelor’s degree in Computer Science or equivalent professional experience

3+ years of proven experience managing geographically distributed software engineering teams

3+ years of experience managing engineering or data teams focused on analytics or data infrastructure

Demonstrated success managing through ambiguity, influencing without direct authority, and leading complex cross-team initiatives

Exceptional stakeholder management and communication skills, capable of clearly articulating vision, progress, and impact

Proven ability to attract, hire, mentor, and retain exceptional engineering talent

Product-focused mindset, with experience shaping product vision, defining roadmaps, and delivering high-impact platform solutions

Strong background in modern data infrastructure and modeling (e.g., SQL, Presto, Spark, Dask, Polars)

Strong understanding of query optimization and performance tuning in SQL and experience with columnar storage formats (e.g., Parquet, ORC)

Demonstrated experience designing normalized and denormalized data structures for analytical workloads

Preferred Qualifications

Familiarity with AWS cloud technologies and on-prem compute clusters (e.g., Slurm, SSH, Unix)

Familiarity with Airflow for data orchestration pipelines

Exposure to quantitative research or machine learning environments

Experience managing operationally critical, high-availability systems, ensuring precision, reliability, and robustness

Expertise in metadata management, data lineage, and applying robust data governance principles