business analytics

Job description

1. business reviews & reporting cadence own weekly, bi-weekly, and monthly business review decks end-to-end: pull data, structure narrative, present to leadership set up and maintain kpi dashboards, product funnels, capex trackers, and north-star metric frameworks from scratch be the single source of truth for business performance — data that goes into leadership reviews and investor conversations originates with you 2. watchtower: anomaly detection & early warning build proactive monitoring systems that flag drops in aum inflows, sip health, cross-sell conversion, funnel leakages, or user portfolio anomalies — before leadership asks track 25+ primary metrics cut by product, cohort, time, and user segment daily diagnose root causes, not just report numbers; propose and drive resolution 3. user & product analytics run funnel, cohort, and user behaviour analysis on the portfolio user base to surface cross-sell, engagement, and monetisation opportunities translate ambiguous business questions into structured analyses with clear recommendations — not just data outputs identify high-propensity user segments and work with product/growth teams to activate them support product decisions with data, including a/b experiments and feature adoption analysis 4. growth & monetisation strategy identify data-led opportunities to improve product cross-sell and business volumes across the wealth product suite build p&l and roi models to evaluate new product launches, campaigns, and partnerships support expansion into new products (global equities, and beyond) with analytical frameworks 5. investor relations data support prepare monthly investor update packs, ad-hoc data briefs on product performance, and materials required for fundraising conversations as the company moves toward ipo, ensure data integrity and narrative consistency across all external-facing numbers you won't have direct investor interaction initially, but your work is what leadership takes into those rooms 6. automation & ai-augmented analytics proactively automate recurring reports using python and ai/agentic frameworks — the bar is reducing manual bandwidth by at least 25% build pipelines that replace repetitive manual effort; comfort with llm-assisted workflows and agentic tools is a real expectation, not a nice-to-have champion a culture of "build once, run forever" for monitoring and reporting