PM Engagement Analyst

Verition Fund Management LLC; New York (NY); On-site; USD 80,000 - 100,000; Full time

Job summary

Verition Fund Management LLC is looking for a highly motivated PM Engagement Analyst to support the senior PM Engagement team within their Long/Short Equity business. This role involves leveraging data and analytics to enhance investment decision-making and research workflows.

The ideal candidate should have a strong analytical mindset, foundational skills in Python/SQL, and experience with large datasets. The analyst will assist with performance analysis, portfolio diagnostics, and contribute to the improvement of internal workflows.

Qualifications

• 2–4 years of experience in financial services with investment teams.
• Foundational proficiency in Python and SQL.
• Comfortable with large datasets and data analysis.

Responsibilities

• Support PM performance and trading behavior analysis.
• Perform ad hoc analysis and portfolio diagnostics.
• Work with factor models and portfolio analytics frameworks.

Skills

Data analysis

Python

SQL

Long/Short Equity understanding

Data visualization

Tools

Barra

Axioma

FactSet

Bloomberg

Job description

Verition Fund Management LLC (“Verition”) is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading.

We are seeking a highly motivated PM Engagement Analyst to support the senior PM Engagement team in their work with Portfolio Managers and analysts within our Long/Short Equity business at a leading multi-strategy hedge fund. This role sits at the intersection of investing, data, analytics, and technology, helping teams leverage data, factor analytics, and internal tools to improve research workflows and investment decision-making. The ideal candidate will have a strong analytical mindset, foundational technical skills in Python and SQL, familiarity with factor models and equity investing, and a desire to work closely with front-office investment professionals in a fast-paced environment.

Key Responsibilities

• Partner directly with senior members of the L/S engagement team to support data-driven workflows analyzing L/S PM performance and trading behavior.
• Support engagement team on ad hoc analysis, portfolio diagnostics, and research tooling.
• Work with factor models and portfolio analytics frameworks to help investment teams better understand exposures, risk, and performance drivers.
• Analyze portfolio positioning, style exposures, and alpha signals across L/S Equity strategies.
• Support workflows related to risk decomposition, factor attribution, and portfolio construction.
• Use Python and SQL to analyze large datasets, automate workflows, and build lightweight analytical tools.
• Help improve internal data workflows and reporting processes for investment teams.
• Work closely with data teams and quant researchers, to identify gaps in workflows and improve the investment process.
• Contribute to the rollout and adoption of internal analytics and research tools.

Required Qualifications

• 2–4 years of experience within financial services, ideally supporting investment teams, research workflows, data analysis, or portfolio analytics.
• Foundational proficiency in Python and SQL
• Comfortable working with large datasets and performing data analysis
• Understanding of fundamental Long/Short Equity investing
• Familiarity with factor models, portfolio analytics, and risk concepts
• Strong judgment and intellectual curiosity
• Ability to not just produce analysis but also present it in a clear and engaging manner

Desirable Skills

• Experience with portfolio/risk platforms such as Barra, Axioma, FactSet, Bloomberg, or similar tools.
• Exposure to alternative data workflows and equity research processes.
• Familiarity with visualization and analytics tools (Plotly, Streamlit, Dash).
• Interest in AI-driven research workflows and modern data tooling.