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Job Description
Data Scientist (Risk Intelligence) Location:
Onsite New York, NY (5 days/week) Position Type:
Full-Time (Permanent) Work Policy:
In-person only (Relocation stipend available; visa sponsorship available) Start Timeline:
ASAP About This is a foundational data science hire within the Risk & Underwriting team. The Data Scientist will focus on developing and productionizing underwriting models, building risk dashboards, and driving portfolio analytics to support scaling of credit offerings while maintaining strong portfolio performance. Why join Join a high-impact role as one of the first data science hires in a fintech startup
Build risk intelligence systems powering credit decisions for e-commerce businesses
Collaborate closely with underwriting and product teams in a fast-paced, high-output environment
Opportunity to expand scope into broader intelligence/AI functions over time
Relocation stipend and visa sponsorship available for exceptional candidates
Compensation Base Salary: $140,000 - $170,000 (flexible for senior candidates)
Equity: 0.05% - 0.10%
Tech environment SQL, Python (or R)
Tools: Hex, Looker, Mode, Metabase
Focus areas: Underwriting models, credit risk analytics, portfolio monitoring, dashboards
Role summary The Data Scientist will partner with underwriting to design, implement, and optimize credit risk models, monitoring tools, and automation workflows. The role requires a mix of strong technical skills, financial acumen, and the ability to operate as a generalist in a lean startup environment. Responsibilities Build dashboards, monitoring tools, and risk models
Automate underwriting and credit assessment workflows
Conduct back-testing and model tuning
Collaborate with underwriting to translate business needs into quantitative insights
Expand scope to broader intelligence/AI functions as the company grows
Must-have qualifications 4+ years of experience in data science, preferably in credit, underwriting, or financial services
Proficiency in SQL and Python (or R)
Strong background in statistics, machine learning, and data modeling
Experience with dashboards and data visualization tools (e.g., Hex, Looker, Mode, Metabase)
Strong communication skills and ability to operate in a generalist startup environment
Ability to work onsite in NYC 5 days/week (relocation possible)
qualifications Experience in e-commerce lending or fintech startups with lending products
Exposure to both fintech and traditional banking environments
Understanding of financial KPIs and ecommerce/fintech datasets
Experience working closely with credit/risk or lending teams
Signals of excellence such as:
Prior experience building end-to-end solutions (side projects, startups, internal tools)
Past founder or community-building experience
Roles with high ownership or multiple hats
Experience in high-output environments such as Cash App, Square, or other top fintechs
Additional desired experience Willingness to work long hours as needed in person in San Francisco
Experience with Docker, Kubernetes, and Terraform
Experience building for scale, ideally at companies where products are self-hosted by customers
Experience with hyperscalers (AWS, GCP, Azure), with a preference for multi-cloud experience
5+ years of experience as a DevOps or Infrastructure Engineer
Ability to work closely with customers, demonstrating patience and friendliness
High attention to detail
High agency and strong propensity to learn
B.S. in Computer Science or equivalent degree, undergraduate or higher
Experience at Series B+ stage companies or later, or smaller companies with very large-scale products
Experience with Linux systems is a plus
Strong background in computer networking
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Data Scientist (Risk Intelligence) Location:
Onsite New York, NY (5 days/week) Position Type:
Full-Time (Permanent) Work Policy:
In-person only (Relocation stipend available; visa sponsorship available) Start Timeline:
ASAP About This is a foundational data science hire within the Risk & Underwriting team. The Data Scientist will focus on developing and productionizing underwriting models, building risk dashboards, and driving portfolio analytics to support scaling of credit offerings while maintaining strong portfolio performance. Why join Join a high-impact role as one of the first data science hires in a fintech startup
Build risk intelligence systems powering credit decisions for e-commerce businesses
Collaborate closely with underwriting and product teams in a fast-paced, high-output environment
Opportunity to expand scope into broader intelligence/AI functions over time
Relocation stipend and visa sponsorship available for exceptional candidates
Compensation Base Salary: $140,000 - $170,000 (flexible for senior candidates)
Equity: 0.05% - 0.10%
Tech environment SQL, Python (or R)
Tools: Hex, Looker, Mode, Metabase
Focus areas: Underwriting models, credit risk analytics, portfolio monitoring, dashboards
Role summary The Data Scientist will partner with underwriting to design, implement, and optimize credit risk models, monitoring tools, and automation workflows. The role requires a mix of strong technical skills, financial acumen, and the ability to operate as a generalist in a lean startup environment. Responsibilities Build dashboards, monitoring tools, and risk models
Automate underwriting and credit assessment workflows
Conduct back-testing and model tuning
Collaborate with underwriting to translate business needs into quantitative insights
Expand scope to broader intelligence/AI functions as the company grows
Must-have qualifications 4+ years of experience in data science, preferably in credit, underwriting, or financial services
Proficiency in SQL and Python (or R)
Strong background in statistics, machine learning, and data modeling
Experience with dashboards and data visualization tools (e.g., Hex, Looker, Mode, Metabase)
Strong communication skills and ability to operate in a generalist startup environment
Ability to work onsite in NYC 5 days/week (relocation possible)
qualifications Experience in e-commerce lending or fintech startups with lending products
Exposure to both fintech and traditional banking environments
Understanding of financial KPIs and ecommerce/fintech datasets
Experience working closely with credit/risk or lending teams
Signals of excellence such as:
Prior experience building end-to-end solutions (side projects, startups, internal tools)
Past founder or community-building experience
Roles with high ownership or multiple hats
Experience in high-output environments such as Cash App, Square, or other top fintechs
Additional desired experience Willingness to work long hours as needed in person in San Francisco
Experience with Docker, Kubernetes, and Terraform
Experience building for scale, ideally at companies where products are self-hosted by customers
Experience with hyperscalers (AWS, GCP, Azure), with a preference for multi-cloud experience
5+ years of experience as a DevOps or Infrastructure Engineer
Ability to work closely with customers, demonstrating patience and friendliness
High attention to detail
High agency and strong propensity to learn
B.S. in Computer Science or equivalent degree, undergraduate or higher
Experience at Series B+ stage companies or later, or smaller companies with very large-scale products
Experience with Linux systems is a plus
Strong background in computer networking
#J-18808-Ljbffr