Man Group
Quant Developer
About this role
Man Group is seeking a Quant Developer in New York to support their discretionary investment and solutions technology teams. The role involves building and maintaining Python-based data pipelines and analytics platforms while collaborating with stakeholders to integrate AI tools into investment workflows.
What you'll do
- Develop and maintain Python data pipelines using libraries like Pandas and NumPy
- Enhance portfolio analytics and fund data platforms
- Contribute to AI-powered research tools and integrations
- Build FastAPI and Flask backends alongside React/TypeScript frontends
- Deploy services on Kubernetes and manage Airflow workflows
- Engage with local stakeholders to translate business needs into tech solutions
What they're looking for
- Proficiency in Python
- Experience with data libraries (Pandas, NumPy)
- Knowledge of web frameworks (FastAPI, Flask)
- Familiarity with frontend technologies (React, TypeScript)
- Understanding of Kubernetes and Airflow
- Experience in AI tools and integrations
- Strong collaboration and communication skills
Benefits
- Opportunity to work with advanced technology
- Collaborative team across multiple locations
- Shape AI integration within investment workflows
- Involvement in production operations and stability
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Man Group
Man Group builds technology platforms and data systems that power investment operations, particularly in private credit and discretionary investing. The company is hiring Software Engineers and Quant Developers to develop full-stack systems, data pipelines, analytics platforms, and AI-powered tools that support investment professionals.
View all jobs at Man GroupLikely interview questions
- Walk us through your experience building and maintaining Python data pipelines in production. How have you handled data quality issues or performance bottlenecks with Pandas/NumPy at scale?
- Describe a time you've worked directly with non-technical stakeholders (like portfolio managers or analysts) to understand their needs and translate them into technical solutions. How did you manage scope or competing priorities?