Senior Finance & Analytics Associate, Private Equity Data

Landing Point; Boston (MA); On-site; USD 95,000 - 110,000; Full time

Job summary

Landing Point is seeking a Senior Finance Associate to join its Global Private Equity Analytics data function in Boston. You will deliver data-driven insights, support fundraising and LP engagement, and help improve processes across the analytics team.

The role emphasizes partnering with Finance, Investor Relations, and IT to understand data needs; you will leverage SQL, Python, and Power BI to automate workflows, build dashboards, and contribute to enterprise data lake governance.

Qualifications

• 2–6 years of accounting/finance experience, eager to move into data and analytics.
• Strong attention to detail and ability to communicate technical/financial logic to diverse audiences.
• Experience with SQL, Python, DAX/Power BI or other data/BI tooling is a plus.
• Exposure to private equity/alternative assets and/or fund/partnership accounting is beneficial.
• CPA or CFA designation is advantageous but not required.

Responsibilities

• Support fundraising and LP engagement by delivering accurate, timely data and analysis in response to investor requests.
• Identify and improve repeatable, manual, or error-prone workflows using tools like Power BI, Alteryx, and scripting.
• Contribute to enterprise-level applications and extend the capabilities of the data platform.
• Partner with the Data Governance team to maintain a well-documented data lake.
• Collaborate with Finance, Investor Relations, Capital Markets, IT, and Investment Professionals to understand data needs.

Tools

SQL

Python

DAX/Power BI

Job description

Landing Point is seeking a Senior Finance Associate to join its Global Private Equity Analytics data function in Boston. You will deliver data-driven insights, support fundraising and LP engagement, and help improve processes across the analytics team.

The role emphasizes partnering with Finance, Investor Relations, and IT to understand data needs; you will leverage SQL, Python, and Power BI to automate workflows, build dashboards, and contribute to enterprise data lake governance.