Data Scientist
7.0/10
Sardine
Not specified
Remote
mid
about 1 month ago
May be outdated
aitechPythonRSparkSQL
AI Summary
The vacancy is strong in task clarity and requirements but lacks specific compensation details.
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Description
Our culture
- •We have hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. However, we maintain a remote-first work culture. #WorkFromAnywhere
- •We hire talented, self-motivated individuals with extreme ownership and high growth orientation.
- •We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.
What you’ll be doing
- •Champion a data-first approach across internal teams and client engagements, promoting clarity and impact
- •Build and deploy machine learning models to prevent fraud across diverse fintech use cases
- •Use data and models to support the development of risk mitigation strategies and interventions while preserving and improving the user experience
- •Work directly with clients to understand challenges and deliver high-impact, data-driven solutions
- •Evolve our risk metrics, the supporting datasets, and how we measure the causal impact of initiatives
- •Collaborate with engineering to scale models into production and optimize performance
Benefits we offer
- •Generous compensation in cash and equity
- •Early exercise for all options, including pre-vested
- •Work from anywhere: Remote-first Culture
- •Flexible paid time off and Year-end break
- •Health insurance, dental, and vision coverage for employees and dependents
- •*US and Canada specific*
- •4% matching in 401k / RRSP
- •*US and Canada specific*
- •MacBook Pro delivered to your door
- •One-time stipend to set up a home office — desk, chair, screen, etc.
- •Monthly meal stipend
- •Monthly social meet-up stipend
- •Annual health and wellness stipend
- •Annual Learning stipend
Requirements
What you’ll need
- •7+ years of experience in data science or quantitative modeling, ideally in risk or fraud contexts
- •Advanced degree in a quantitative field (Mathematics, Statistics, Computer Science, Engineering, Economics, etc.)
- •Strong working knowledge of Python, R, Spark, SQL, or equivalent
- •Sharp critical thinking and creative problem-solving skills with a bias toward action
- •Proven ability to explain complex technical findings to non-technical stakeholders and clients
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