Pay
$118K–$194K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,819 postings in the last year. Stated ranges, not salaries paid.
NYC Office · New York, United States
Live, first seen by us 71 days agoLocation type: On-siteFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Product & Technology › ML/AIFrom the employer’s posting
Do you require visa sponsorship to work legally in the United States (now or in the future)? This includes needing sponsorship for CPT, OPT or other visa types to work in the US.From the employer’s application form
Improve demand and sales forecasts across thousands of noisy retail time series
Measure promotion lift, price elasticity and cannibalization
Build statistical checks that keep models accurate as messy data arrives
Move exploratory analysis into production-grade models with AI/ML engineers
improving prediction quality across thousands of noisy, real-world retail time series
measuring lift, price elasticity, and cannibalization so brands know which promotions actually pay
building the statistical checks that keep our models honest as messy data flows in
You'll work alongside our AI/ML engineering team to move from exploratory analysis to production-grade insight
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 can explain a model to a non-technical brand operator and defend it to an ML engineer
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$118K–$194K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,819 postings in the last year. Stated ranges, not salaries paid.
Day 71
Up longer than most. Similar jobs usually come down between day 7 and day 57.
From 10,789 similar postings that came down. Coming down is not always a hire.
10 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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
- Familiarity with forecasting at scale (hierarchical forecasting, intermittent demand) Stack: Python · SQL · Snowflake · dbt · AWS 🌴 Perks + Benefits
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New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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.
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.
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
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
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
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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New York, United States
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