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Salary
$250k – $300k per year
Location
In office (New York)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Confido is the AI infrastructure for CPG brands, providing a single source of truth for accounting, finance, sales, and operations teams.

Confido is the AI infrastructure powering modern CPG - the platform that 200+ brands like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana use to run everything from deductions to production planning. Finance, accounting, sales, and operations, unified in one system for the first time.

We're growing 5x year over year with a small team in New York City; the people who join now will shape the product, the culture, and the company itself.

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

THE ROLE

CPG brands live and die by their ability to predict what’s coming - how much product will sell, where demand will land, and what a promotion will actually do to the business. At Confido, you’ll build models that help brands forecast sales, price products, and shape promotional strategy. You’ll work with an unusually broad dataset spanning sell-through, inventory, deductions, trade promotions, and supply-chain signals from 200+ brands - much of it messy, real-world data that makes the problems genuinely interesting. The models you build will directly influence decisions behind the products you see on store shelves every day.

As a Data Scientist, you'll turn that data into models and analyses that ship inside the product - not slide decks. You'll work alongside our AI/ML engineering team to move from exploratory analysis to production-grade insight.

What you'll work on

  • Demand and sales forecasting - improving prediction quality across thousands of noisy, real-world retail time series

  • Promotion effectiveness - measuring lift, price elasticity, and cannibalization so brands know which promotions actually pay

  • Data quality and evaluation - building the statistical checks that keep our models honest as messy data flows in

About you

  • 5+ years of hands-on data science experience with real-world (not benchmark) data

  • Strong statistical foundations: regression, time-series methods, experiment design, uncertainty quantification

  • Fluent in Python and SQL; comfortable working in a modern data stack (we use Snowflake and dbt)

  • You care whether your analysis is right, not just whether it runs - you validate, sanity-check, and communicate uncertainty

  • You can explain a model to a non-technical brand operator and defend it to an ML engineer

Bonus

  • Experience with retail, CPG, supply chain, or demand-planning data

  • Experience shipping models into production systems (vs. offline analysis only)

  • Familiarity with forecasting at scale (hierarchical forecasting, intermittent demand)

Stack: Python · SQL · Snowflake · dbt · AWS

Perks + Benefits

  • Equity - own a meaningful piece of the company you’re helping build

  • Fully paid health coverage through Aetna - we cover 100% of employee premiums

  • Top-tier dental and vision coverage through Guardian

  • Carrot Fertility Pro - comprehensive fertility and family-forming support

  • 12 weeks of paid parental leave

  • Unlimited PTO - plus regular 4-day holiday weekends we actually take

  • 401(k) through Vestwell

  • Paid relocation support - we’ll help you make the move to NYC

  • Fully equipped workspace from day one - laptop, monitor, keyboard, and a $200 stipend to personalize your setup

  • Team perks - catered Friday lunches, team dinners, and unlimited coffee + snacks featuring products from the brands we work with

Confido provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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