Role Overview
Join BAM’s Portfolio Manager Success team, a global group of data analysts, data scientists, and content experts dedicated to empowering our Portfolio Managers (PMs) and Analysts with world-class data solutions, technical enablement, and hands-on support. As a Portfolio Manager Success Specialist, you will serve as a trusted partner to investment professionals, proactively anticipating their needs and delivering innovative solutions that drive investment performance.
This business-facing, high-impact role offers exposure to front office, technology, and infrastructure teams within a premier multi-strategy fund. If you are naturally curious, passionate about data, and driven by learning new skills, this is the role for you.
Key Responsibilities
- User Enablement & Support: Act as the primary point of contact for PMs and Analysts, providing high-touch support, training, and enablement for BAM’s suite of data products, data pipelines, and analytic tools.
- Data Delivery & Integration: Facilitate the delivery, analysis, and integration of financial, market, and alternative datasets using Python, SQL, and modern cloud tools (e.g., AWS, Airflow, Git).
- Workflow Automation & Best Practices: Collaborate with analytics and engineering teams to automate data workflows, improve knowledge bases, and educate users on data-driven best practices.
- Stakeholder Collaboration: Connect stakeholders across the firm to identify solutions, champion product enhancements, and share knowledge globally.
- Knowledge Management: Maintain and expand BAM’s Knowledge Base and training materials based on user feedback and your own experience supporting diverse investment workflows.
- Incident Management: Deliver high-quality, proactive incident management and service delivery, ensuring timely resolution of user issues and continuous improvement of support processes.
Qualifications & Requirements
- Experience: 2–4 years of professional experience in a data support, application support, customer success, or engineering support function—ideally within financial services, a hedge fund, or investment bank.
- Education: Bachelor’s or Master’s degree in Mathematics, Data Science, Data Engineering, Computer Science, Economics, Finance, or a related field (or equivalent relevant experience).
Technical Skills:
- Proficiency in Python for data analysis and wrangling.
- Working knowledge of SQL and relational databases.
- Familiarity with cloud platforms (AWS preferred), Git, and workflow orchestration tools (e.g., Airflow) is a plus.
- Understanding of time-series, market, and alternative datasets, and their application to quantitative and fundamental investment analysis.
- Problem Solving: Demonstrated expertise in troubleshooting, creative problem-solving, and stakeholder communication (both written and verbal).
- Attention to Detail: High degree of accuracy and attention to detail in all aspects of work.
- Communication: Strong oral and written communication skills, with the ability to translate technical concepts for both technical and non-technical audiences.