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Confido is an AI infrastructure platform serving 200+ CPG brands (including OLIPOP, Simple Mills, Dr. Squatch, Tropicana) with unified finance, accounting, sales, and operations capabilities. The company is growing 5x year-over-year with a small team in NYC.
As Head of Predictions & Optimization, you will build and lead Confido's data science function, starting with the Revenue Growth Management (RGM) product area. You will own the models that translate detailed business insights into actionable decisions for brands, and you will grow the team to 3+ data scientists.
Key responsibilities include:
- Lead pricing and trade optimization for RGM, including price elasticity modeling, promo lift analysis, cannibalization effects, and halo effects to answer "how much should I charge for this?"
- Build promotion recommendations with specificity: duration (4 vs. 8 weeks), discount type (deeper discount, BOGO, buy-3-get-1), and targeting by region, retailer, and account
- Transform predictions into prescriptions by building optimization models that respect real-world constraints (trade budgets, margin targets, retailer calendars)
- Measure actual outcomes using post-event analysis, causal inference, and baselines that brands trust enough to act on
- Partner with AI/ML engineers to move models to production; establish standards for backtesting, evaluation, and monitoring
- Build and mentor the data science team; set technical roadmap alongside CTO and AI research lead
Confido has access to rich proprietary data most competitors lack: shipments, depletions, inventory, consumption, shelf data, merchandising, deductions, store-level demographics, and forward-looking promo plans across hundreds of brands.
REQUIREMENTS:
Required:
- 7+ years of applied data science or predictive modeling, including experience leading projects or people
- Deep expertise in statistical modeling and ML for pricing, demand, or forecasting (elasticity, causal inference, uplift modeling)
- Experience building optimization or decision-support models beyond predictions alone
- Strong Python and SQL with rigor around validation; ability to avoid leakage and distrust suspicious results
- Ability to translate models into clear recommendations non-technical business users will act on
Nice to have:
- RGM, trade promotion, pricing, or revenue management experience in CPG, retail, or marketplaces
- Experience with syndicated or retailer data (Nielsen, SPINS, Circana, retailer POS)
- End-to-end model-to-production experience
- Operations research or mathematical optimization (MIP, solvers)
- Startup or 0-to-1 team-building experience
