Job Specifications
Job Title: Data Science Manager
About the Company:
We're a fast-growing, mission-driven technology company building intelligent solutions to transform how identity and risk are managed across high-stakes industries. Our real-time tools are used to verify identities and prevent fraud at scale--powering secure transactions and building trust between businesses and users. Backed by top-tier investors and recognized in leading industry publications, we're expanding rapidly and looking for curious, driven leaders to join our team.
About the Role:
As a Data Science Manager, you'll lead a team of full-stack data scientists responsible for building and deploying core machine learning models used in fraud detection and financial risk mitigation. You'll play a dual role as both a technical contributor and people leader--driving key initiatives hands-on while supporting your team's development and execution. This is a high-impact, highly cross-functional role requiring strong technical acumen, a product-focused mindset, and a desire to lead in a fast-paced environment.
This is a remote position open to candidates based in the U.S.
Key Responsibilities:
Manage and grow a team of 2-6 full-stack data scientists.
Act as a hands-on leader, contributing to high-leverage modeling, experimentation, and production work.
Guide project planning, timelines, and cross-functional collaboration with product, engineering, and executive leadership.
Build and iterate on machine learning models from end to end--including data acquisition, feature engineering, model training, deployment, and monitoring.
Lead efforts to detect new types of fraudulent activity and expand the company's product offerings.
Drive research and development initiatives that integrate new data sources, improve model accuracy, and inform broader business decisions.
Write reliable, production-quality code used for real-time decision-making.
Develop analytical frameworks to support strategy across data, operations, product, marketing, and sales.
Preferred Qualifications:
10+ years of experience in data science or applied machine learning with a Master's degree, or 5+ years with a PhD.
3+ years of experience directly managing data science teams.
Startup or high-growth company experience strongly preferred.
Demonstrated success solving complex business problems with ML and statistical methods.
Skilled in end-to-end development: defining goals, getting stakeholder alignment, building solutions, and delivering results.
Expertise in core ML/statistics concepts with the ability to implement and iterate quickly; familiarity with cutting-edge techniques a plus.
Proficiency in Python and experience writing production-ready code.
Strong communication skills and the ability to present work to executive stakeholders.
Interest in developing domain knowledge in fraud prevention, identity, or risk; prior experience is a bonus but not required.
Attention to detail and a bias toward thoughtful, business-minded decision-making.
Ability to thrive in a fast-moving environment with a high degree of ambiguity.
Tech Stack:
Python, PostgreSQL, AWS (EC2, S3, RDS, Redshift)
Eligibility:
Must be legally authorized to work in the United States and currently reside in the U.S.
Benefits:
Fully paid health insurance for employees and dependents
401(k) plan with company match (or regional equivalent)
Flexible paid time off
In-person company retreats and team events
Home office setup stipend and additional perks
About the Company
Kadence - we power the creation & adoption of ethical A.I with community driven talent solutions.
Kadence was created to provide exceptional talent to power the AI revolution whilst allowing fair market access for under-represented talent pools. We are developing innovative product offerings, alongside traditional talent models that will support both candidates & clients in this initiative.
We are proud to work with clients developing AI or those looking to hire talent that will support the development & execution of th...
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