Product Manager, Quantitative Product

United Kingdom·Londonmid

Product ManagementProduct Manager

0 views0 saves0 applied

Apply Now

Quick Summary

Overview

Over the last 20 years, Ares’ success has been driven by our people and our culture. Today, our team is guided by our core values – Collaborative, Responsible, Entrepreneurial, Self-Aware,

Technical Tools

Product ManagementProduct Manager

Ares is seeking an Assistant Vice President-level Quantitative Product lead to help define and deliver the product strategy for quantitative investment technology across the firm's global investment platform.

The role sits within Investment Technology Product Management and serves as the product liaison to Ares' global quantitative teams, including Ares' Quantitative Research teams, recognizing that these teams have distinct investment objectives, research methods, tooling requirements, and coverage across a diverse universe of assets, funds, portfolios, and other securities.

In addition to supporting the quant groups directly, the role will act as a catalyst for extending relevant quantitative tools, techniques, data practices, and analytical capabilities into other Ares asset classes and business lines. The individual will identify where proven approaches can be adapted and scaled horizontally, helping embed the quant teams more deeply into the wider organization and increasing the contribution of these functions to investment decision-making across the firm.

The Quantitative Product lead will own product activities from workflow discovery and use-case definition through prioritization, solution design, delivery, adoption, and value realization. The role will assess the process, data, model, and application landscape; distinguish common capabilities from strategy-specific requirements; and determine when solutions should be built, bought, reused, or adapted across teams.

The successful candidate will combine strong product judgment with sufficient quantitative and technical depth to understand models, data dependencies, investment context, and to work effectively with quantitative engineers and investment professionals.

Responsibilities

~1 min read

Quantitative Product Strategy & Roadmap

Define and maintain the product strategy and roadmap for quantitative investment capabilities, aligned with business priorities and the broader Investment Technology architecture.
Translate the distinct objectives of Quantitative groups into sequenced product themes, clear outcomes, and an appropriate balance of shared and strategy-specific capabilities.
Make evidence-based build, buy, reuse, adapt, and retire recommendations in partnership with investment teams, engineering, architecture, and Data & AI.

Workflow Discovery & Use-Case Development

Map end-to-end workflows across research, data acquisition, signal generation, scenario analysis, portfolio construction, execution support, monitoring, and performance feedback.
Develop well-structured use cases and product requirements covering the decision supported, users, data, value, risks, dependencies, controls, and adoption path.
Prioritize opportunities through the firm's intake process based on strategic alignment, value, scalability, technical and data readiness, risk, and organizational readiness.

Quantitative Domain Development

Shape products supporting returns forecasting, liquidity and cash-flow management, hedging and portfolio optimization, risk-adjusted asset allocation, predictive signals, portfolio construction, and monitoring.
Define requirements for scalable ingestion and use of private/public company, market, reference, alternative, portfolio, and third-party datasets.
Build connections between quantitative teams and the wider firm, enabling knowledge transfer, common standards, and greater reuse of institutional expertise.

Product Delivery, Adoption & Value

Champion a user-centric product approach, ensuring quant capabilities are designed around investor workflows and provide measurable improvements to investment decision-making.
Partner with Quantitative Engineering and other technology teams to move solutions from hypothesis and pilot into scalable, resilient, and maintainable products/services.
Establish adoption plans with business sponsors and define and track measures such as decision-cycle time, research throughput, model or component reuse, forecast quality, adoption, control effectiveness, and business value.

Governance, Partnership & Culture

Coordinate with Data & AI, architecture, cyber, infrastructure, risk, operations, legal, compliance, and vendor teams where products depend on shared platforms or require specialist review.
Represent quantitative product priorities in Investment Technology, Data & AI, and use-case governance forums, providing transparent rationale for roadmap and investment decisions.
Build trusted relationships with investment team members, quantitative engineers, risk professionals, and operations teams across regions.