Home › Companies › Imprint › Staff Data Scientist
Staff Data Scientist
Imprint · New York City · Hybrid · Active · Ashby
Job facts
| Field | Value |
|---|---|
| Company | Imprint |
| Title | Staff Data Scientist |
| Normalized title | - |
| Department / team | Engineering / Engineering, Data & Analytics |
| Location | New York City, NY, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Imprint. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York City. | Open |
| Department jobs | Active postings in Engineering. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Imprint |
| Source | dddf0162-741b-457d-9ad0-604e43363e32 |
| ATS provider | Ashby |
Description
Who We Are Imprint is reimagining co-branded credit cards & financial products to be smarter, more rewarding, and truly brand-first. We partner with companies like Crate & Barrel, Rakuten, Booking.com, H-E-B, Fetch, and Shell to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. Our platform combines advanced payments infrastructure, intelligent underwriting, and seamless UX to help brands offer powerful financial products—without becoming a bank.
Co-branded cards account for over $300 billion in U.S. annual spend—but most are still powered by legacy banks. Imprint is the modern alternative: flexible, tech-forward, and built for today’s consumer. Backed by Kleiner Perkins, Thrive Capital, and Khosla Ventures, we’re building a world-class team to redefine how people pay—and how brands grow. If you want to work fast, solve hard problems, and make a real impact, we’d love to meet you.
Learn more about us on Imprint's Technology blog .
Role Summary The Data team at Imprint builds the data foundation that powers smarter, faster decision-making. The team develops infrastructure and analytics systems that support both daily operations and long-term strategy, enabling high-quality insights into customer behavior, product performance, and business growth.
As a Staff Data Scientist , you will own end-to-end analytical projects that directly influence product decisions, marketing campaigns, and executive strategy. You will apply rigorous statistical methods, experimentation design, and predictive modeling to improve customer lifetime value, accelerate feedback loops, and drive measurable business outcomes.
This role blends deep technical expertise with strong business partnership. You will work across the organization—collaborating with product, marketing, and commercial teams—to design experiments, build segmentation frameworks, and translate complex data into clear narratives that shape how Imprint grows. Increasingly, that means building not just analyses but AI-powered systems that can autonomously explore data, generate insights, and operationalize decisions.
What Success Looks Like in the First 90 Days
Shipped a new model to production that drives a measurable business outcome
Delivered a meaningful analysis of a complex business problem, beyond simple A/B test reporting
Fully integrated with the Data Science team through active participation in code reviews, technical discussions, and knowledge sharing
Built strong working relationships with key stakeholders and aligned on priorities with your manager and cross-functional partners
Demonstrated fluency with Imprint's business model, data systems, and user personas—able to explain how the company generates revenue, which partnerships are healthiest, and how your work drives impact
Responsibilities
Apply statistical inference, causal analysis, and experimentation design to improve LTV/CAC and accelerate feedback loops
Champion A/B testing by partnering with cross-functional teams to design, analyze, and interpret experiments rigorously, using scalable frameworks and tooling
Build segmentation frameworks and predictive models (churn, LTV, propensity, etc) to drive targeting, personalization, and lifecycle optimization
Design and build agentic workflows to automate the data science lifecycle (exploration, modeling, experimentation)
Use LLMs and AI tools as collaborators to reason about data, generate hypotheses, and iterate on analyses
Build AI-driven systems for monitoring, diagnosing, and automating business insights and decisions
Translate data into clear narratives that influence product decisions, marketing campaigns, and executive strategy
Support automation projects as needed, including anomaly detection, partner data reporting, and internal self-serve tools or dashboards
Own projects end-to-end - from problem definition through implementation, deployment, and monitoring - while collaborating cross-functionally to drive impact
Contribute to team excellence through code reviews, technical mentorship, and process improvements
Qualifications Required
7-12+ years (depending on leveling & education) of experience in data science, analytics, or a related field—ideally at a high-growth startup or fintech company
Graduate degree in a relevant field (statistics, engineering, science, finance, etc)
Strong Python and SQL skills, with the ability to transform raw data and build custom datasets when needed
Highly analytical mindset with a bias toward action and a relentless focus on getting the numbers right
Ability to clearly communicate complex findings to technical and non-technical audiences
Comfort owning projects end-to-end and collaborating cross-functionally to drive impact
Full-stack problem-solving orientation—eager to dive into messy data, test and validate assumptions, and question everything in pursuit of a solution
Nice to Have
Experience building or scaling experimentation infrastructure
Experience building or improving ML infra
Familiarity with dashboarding tools such as Sigma or Looker
Experience in credit, lending, or card products
Exposure to lifecycle marketing or prescreen modeling
Background in time series analysis, forecasting, optimization, or simulation
Location & Work Model
This is a hybrid role requiring 2–3 days per week onsite
Open to candidates based in or willing to relocate to San Francisco or New York City
Perks & Benefits Competitive compensation and equity packages
Leading configured work computers of your choice
Flexible paid time off
Fully covered, high-quality healthcare, including fully covered dependent coverage
Additional health coverage includes access to One Medical and the option to enroll in an FSA
20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents
Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity
Imprint is committed to a diverse and inclusive workplace. Imprint is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Imprint welcomes talented individuals from all backgrounds who want to build the future of payments and rewards. If you are passionate about FinTech and eager to grow, let’s move the world forward, together.
Full job record
| Job ID | a3e5f4207b5d12bbed7ab1101362689d04219ddc |
| Org ID | 5f97dae1-ca2c-4003-b3bc-3a4e3e05e6fe |
| Source ID | dddf0162-741b-457d-9ad0-604e43363e32 |
| Board ID | dddf0162-741b-457d-9ad0-604e43363e32 |
| Provider | ashby |
| Provider Job Key | 9c95a7fc-0d5f-4dd3-9422-3cb528efa29f |
| Title | Staff Data Scientist |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | New York City |
| Department | Engineering |
| Team | Engineering, Data & Analytics |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | NY |
| City | New York City |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/imprint/9c95a7fc-0d5f-4dd3-9422-3cb528efa29f |
| Apply URL | https://jobs.ashbyhq.com/imprint/9c95a7fc-0d5f-4dd3-9422-3cb528efa29f/application |
| First Seen At | 2026-05-29 07:14:44Z |
| Last Seen At | 2026-06-06 09:35:03Z |
| Last Checked At | 2026-06-06 09:35:03Z |
| Last Changed At | 2026-05-29 07:14:44Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=imprint/date=2026-06-06/2026-06-06T09-34-51-834Z-86a39b13aea52cb4f3e5bb0f91eafe9a733d288ae8716af0678c4f154ef56452.json |
Event Fields
{
"content_hash": "017149cf328d05e98ef9a876c5d21acba4860cdff7d2d9b1b6f9b53edaf6bf7e",
"source_hash": "ceacde78ed7a08dcfa523abf06007f1e26734a1ba8a1df0a4ffdb07905b83de7",
"last_changed_at": "2026-05-29T07:14:44.714Z",
"active_status": "active"
}Parsed Structured
{
"language": "en",
"location": {
"raw": "New York City",
"city": "New York City",
"region": "NY",
"country": "United States",
"is_remote": false,
"confidence": 0.75
},
"salary_max": null,
"salary_min": null,
"inferred_at": "2026-06-06T09:35:03.706Z",
"launch_scope": {
"reason": "english_us_canada",
"included": true,
"language": "en",
"location": {
"raw": "New York City",
"city": "New York City",
"region": "NY",
"country": "United States",
"is_remote": false,
"confidence": 0.75
},
"countries": [
"United States"
]
},
"remote_policy": "hybrid",
"salary_period": null,
"workplace_type": "hybrid",
"salary_currency": null
}Extensions
{}Native Structured
{
"id": "9c95a7fc-0d5f-4dd3-9422-3cb528efa29f",
"team": "Engineering, Data & Analytics",
"title": "Staff Data Scientist",
"jobUrl": "https://jobs.ashbyhq.com/imprint/9c95a7fc-0d5f-4dd3-9422-3cb528efa29f",
"address": null,
"applyUrl": "https://jobs.ashbyhq.com/imprint/9c95a7fc-0d5f-4dd3-9422-3cb528efa29f/application",
"isListed": true,
"isRemote": false,
"location": "New York City",
"updatedAt": null,
"apiVersion": "ashby-non-user-graphql-v1",
"department": "Engineering",
"publishedAt": null,
"workplaceType": "Hybrid",
"employmentType": "FullTime",
"secondaryLocations": [
{
"location": "San Francisco"
}
]
}Get this page with API
Rendered from the bluedoor Job Postings API. Reproduce it:
GET https://api.bluedoor.sh/job-postings/v1/jobs/a3e5f4207b5d12bbed7ab1101362689d04219ddc?include=descriptionJSONGET https://api.bluedoor.sh/job-postings/v1/orgs/5f97dae1-ca2c-4003-b3bc-3a4e3e05e6feJSONGET https://api.bluedoor.sh/job-postings/v1/sources/dddf0162-741b-457d-9ad0-604e43363e32JSONGET https://api.bluedoor.sh/job-postings/v1/jobs/a3e5f4207b5d12bbed7ab1101362689d04219ddc/eventsJSON