Senior Associate, Product Owner - Analytics & Data Strategy, Wealth Management

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, Trustworthy – and our purpose to be a catalyst for shared prosperity and a better future. Through our recruitment, career development and employee-focused programming, we are committed to fostering a welcoming and inclusive work environment where high-performance talent of diverse backgrounds, experiences, and perspectives can build careers within this exciting and growing industry.

Job Description

Ares is seeking a dynamic and experienced professional to help define and execute the analytics & data strategy for Ares Wealth Management Solutions.  Your work will ensure insights are trusted, timely, and embedded in how our teams serve our clients and investors. You’ll act as a product owner across the analytics stack—partnering with Technology, Sales, and Marketing—to turn data into decisions, and decisions into growth. 

Key Responsibilities 

Analytics strategy & roadmap 

• Establish a multi‑year analytics strategy aligned to WMS priorities, covering the full stack: Platforms → Data Integration → Reporting → Intelligence (AI/ML); convert it into a quarterly roadmap with outcomes and KPIs. 

• Prioritize the portfolio (dashboards, models, signals, and data products) using a clear intake and governance process; socialize trade‑offs with stakeholders. 

Data management & quality 

• Lead WMS data management by partnering with Ares IT and vendors to establish an ownership model, data contracts, lineage, access controls, SLAs, and data quality rules. 

• Partner with Tech/IT to modernize pipelines and metadata; 

Product ownership for insights 

• Own the backlog and development for key analytics products (e.g. advisor segmentation, coverage optimization, campaign attribution, and sales activity efficacy). 

• Drive self‑service BI—define certified data sources, semantic layers, and standards so teams can answer 80% of questions without analyst handoffs. 

Advanced analytics & AI enablement 

• Introduce pragmatic ML/AI where it moves the needle (propensity models, lead scoring, opportunity recommendations, content personalization); measure incremental lift and adoption. 

• Partner with enterprise AI and Data programs to tap shared capabilities while tailoring for WMS use 

• Publish monthly newsletter “Insights that matter.” 

Success looks like (first 6–12 months) 

• A signed‑off analytics strategy and operating model, with a live quarterly roadmap and published OKRs. 

• Critical WMS datasets have owners, SLAs, DQ monitors, and a visible backlog 

• 2–3 priority insight products in production with >60–75% monthly active use from target personas; measurable improvements in seller focus (time-on-selling), coverage, or conversion. 

• Certified semantic layer(s) powering the top WMS dashboards; ad‑hoc requests decrease as reuse increases. 

Qualification 

• 5+ years of experience in roles across analytics, data product management, or data strategy (financial services or B2B distribution preferred). 

• Hands‑on expertise with Salesforce, Tableau, Data Bricks, Alteryx and SQL (certifications preferred); familiarity with Python/ML workflows a plus. 

• Experience imple