NM Capital - Investment Data Analyst

Northwestern Mutual•Milwaukee, WI

6d•$75,600 - $130,440

About The Position

This role will focus on the data associated with NMC’s investment transaction lifecycle; including deal sourcing, due diligence, valuation, portfolio monitoring, portfolio performance, and reporting to clients. The analyst will manage, transform, and integrate portfolio and benchmark data to support advanced quantitative analysis, ensuring information is accurate, auditable, and analytically robust. They will develop and maintain investment performance measurement frameworks, including returns, benchmarks, attribution, and performance drivers at the asset, strategy, and portfolio level. The role involves designing and delivering custom analyses and models to answer ad-hoc investment, portfolio management, and investor questions, as well as identifying, defining, and refining key investment metrics and analytical views that inform investment decisions and support positive business outcomes. Building and maintaining Power BI dashboards that combine quantitative outputs and visual storytelling to support portfolio management and senior leadership is a key responsibility. The analyst will partner with investment, finance, and investor relations teams to support due diligence, investor requests, marketing materials, and quarterly performance reporting. Engaging users with analytically rigorous tools and datasets, creating a virtuous cycle where insights drive adoption and improved data quality, is also part of the role. Additionally, the analyst will configure eFront and assist users with troubleshooting and best practices, contribute to the design and maintenance of AI-ready datasets by optimizing and enhancing datasets for consumption by investment professionals, and clearly document analytical methodologies, assumptions, data standards, and repeatable processes.

Requirements

Bachelor’s and/or master’s degree in Finance, Economics, Statistics, Data Science, Computer Science, Financial Engineering, or a related quantitative field, or an equivalent combination of education and experience.
Two or more years of experience in a quantitative, analytics, investment, or performance measurement‑focused role.
Experience with investment performance measurement, return calculations, or portfolio analytics.
Strong data‑driven decision‑making mindset with comfort working in ambiguous, unstructured problem spaces.
Process‑oriented approach with the ability to design scalable, repeatable analytical solutions.
Intellectual curiosity and willingness to challenge assumptions, methodologies, and existing analytical approaches.
High attention to detail and a strong instinct to reconcile, validate, and pressure‑test data and results.
Strong proficiency in Python for data analysis, including pandas, numpy, and analytical workflows.
Experience building custom investment analyses, performance calculations, and repeatable analytical pipelines.
Proficiency in Power BI, including data modeling and integrating quantitative outputs into dashboards.
Advanced proficiency in Excel, including modeling and validation of analytical results.
Ability to interpret, scrub, process, and clearly explain complex quantitative results to non‑technical stakeholders

Nice To Haves

Experience with Snowflake, Python, dbt, and PowerBI preferred.
Proficiency in Snowflake and dbt to query and build datasets.

Responsibilities

Manage, transform, and integrate portfolio and benchmark data to support advanced quantitative analysis, ensuring information is accurate, auditable, and analytically robust.
Develop and maintain investment performance measurement frameworks, including returns, benchmarks, attribution, and performance drivers at the asset, strategy, and portfolio level.
Design and deliver custom analyses and models to answer ad‑hoc investment, portfolio management, and investor questions.
Identify, define, and refine key investment metrics and analytical views that inform investment decisions and support positive business outcomes.
Build and maintain Power BI dashboards that combine quantitative outputs and visual storytelling to support portfolio management and senior leadership.
Partner with investment, finance, and investor relations teams to support due diligence, investor requests, marketing materials, and quarterly performance reporting.
Engage users with analytically rigorous tools and datasets, creating a virtuous cycle where insights drive adoption and improved data quality.
Configure eFront and assist users with troubleshooting and best practices.
Contribute to the design and maintenance of AI‑ready datasets by optimizing and enhancing datasets for consumption by investment professionals.
Clearly document analytical methodologies, assumptions, data standards, and repeatable processes.