Head of Predictions & Optimization

The brands on your kitchen shelf are run by people doing extraordinary work that nobody sees.

We're building the platform they run on, and a brand they'll be proud to be part of.

Confido is the AI operating system that runs cash application, deductions, trade and planning in one place for CPG brands. That means Finance, Sales, and Ops finally work on the same number.

We’re trusted by 250+ brands managing $30B+ in revenue, including Daisy, OLIPOP, Simple Mills, Idahoan, and more. We've achieved best-in-class growth and recently raised a $55M Series B led by Insight Partners to accelerate our momentum.

If you want your work on shelves everywhere — and outsized ownership while you build — we'd love to meet you.

THE ROLE

Tell brands what to charge, which promotions to run, and where. Back it with data almost no one else has.

Confido sees what's actually happening in the physical world of CPG: shipments, depletions, inventory, consumption, what's on the shelf, merchandising, deductions, the demographics of who lives near each store, and forward-looking promo plans. That means rich actuals and a real view of the future, across hundreds of brands. Most of this data isn't publicly available anywhere.

As Head of Prediction & Optimization, you'll build and lead Confido's data science function, starting with our newest product area: Revenue Growth Management (RGM). You'll own the models that turn a detailed picture of the business into decisions brands actually act on, and you'll grow the team to 3+ data scientists.

Location: New York, NY (Relocation supported)

WHAT YOU'LL DO

• Lead pricing and trade optimization for RGM, including price elasticity, promo lift, cannibalization, and halo effects, so you can answer "how much should I charge for this?"

• Build promotion recommendations that get specific. Should a promo run 4 weeks or 8? Should it be a deeper discount, a BOGO, or buy-3-get-1? Which regions, retailers, and accounts should get it?

• Turn predictions into prescriptions by building optimization that works under real constraints like trade budgets, margin targets, and retailer calendars

• Measure what actually worked, using post-event analysis, causal inference, and baselines that brands trust enough to change their plans

• Partner with our AI/ML engineers to take models to production, and set the bar for backtesting, evaluation, and monitoring

• Build the team: hire and mentor data scientists, and set the roadmap and technical direction alongside our CTO and AI research lead

WHAT WE'RE LOOKING FOR

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