Associate, Business Intelligence - Global Private Wealth (EMEA & APAC)

For over forty years, HarbourVest has been home to a committed team of professionals with an entrepreneurial spirit and a desire to deliver impactful solutions to our clients and investing partners. As our global firm grows, we continue to add individuals who seek a collaborative, open-door culture that values diversity and innovative thinking.

In our collegial environmentthat’smarked by low turnover and high energy,you’llbe inspired to grow and thrive. Here, you will be encouraged to build on your strengths andacquirenew skills and experiences.

We are committed to fostering an environment of inclusion that promotes mutual respect among all employees. Understanding and valuing these differencesoptimizesthe potential of both the individual and the firm.

HarbourVest is an equal opportunity employer.

This position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically13 weeksper quarter), leaving 5additionalremote days to be used as needed.

HarbourVest is seeking an outstanding individual to join our dynamic team as an Associate, Business Intelligence - Global Private Wealth (EMEA & APAC). This role offers the chance to work with world-class professionals in a collaborative and inclusive environment. Your contributions will directlyimpactour success.

What you will do:

• Own the integrity and commercial usability of GPW opportunity data within Salesforce and related reporting environments to ensurean accuratesingle sourceof truth.

• Maintain and continuously improve pipeline hygiene, definitions, and stage rigor in partnership with regional sales teams.

• Produce rigorous pipeline analysis covering conversion, velocity, coverage, and gap-to-target views across regions, channels, and products.

• Identifystructural issues, risks, and whitespace within the pipeline and convert analysis into clear, actionable recommendations.

• Partner with sales and other collaborators to connect sales activity, engagement, and pipeline conversion into business insights.

• Be a key contributor to analysis across regional fundraising campaigns, engagement trends, and efficiency initiatives.

• Support forecasting, pacing, and performance discussions with objective data rather than anecdotal updates.

• Serve as a link between regional sales teams and central commercial reporting, ensuring alignment with global definitions and frameworks.

• Contribute to quarterly business reviews, monthly senior leadership reporting, and ad hoc deep dives asrequired.

• Support the evolution of scalable distribution reporting and analytics frameworks across CRM and enterprise data environments.

• And other responsibilities asrequired.

What you bring:

• Strong analytical and quantitative skills witha high levelof attention to detail.

• Advanced comfort working with Salesforce reporting, dashboards, and data extraction (Excelproficiencyessential; BI tools a strong plus).

• Ability to distill, structure and communicate insights clearly to non-technical collaborators.

• Strong commercial judgment and ability tofocusanalysis on decisions and outcomes, not just outputs.

• Comfort working in a fast-paced, evolving environment with multiple collaborators and competing priorities.

• Ability to see the bigger picture whilemaintainingdisciplined execution on data quality and process.

• Excellent written and verbal communication skills.

• High personal standards, strong work ethic, and a mentality of continuous improvement.

Education Preferred

• BS/BA degree or equivalent experience.

• MBA, CFA, or CAIA beneficial but notrequired.

Experience

• 3-5 years’ experience in commercial operations, sales analytics, strategy, or performance analytics within asset management, private markets, or financial services.

• Prior experience supporting fundraising, pipeline management, or sales enablement functions strongly preferred.