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About the role
You will own end-to-end modeling strategy for domains like credit, risk, or growth while driving models into production. Additionally, you will set technical standards, mentor team members, and translate business strategy into a coherent data science roadmap.
What they look for
Requirements
Candidates must have 5+ years of hands-on data science or applied ML experience with a track record of owning production systems. Proficiency in Python, SQL, and strong statistical grounding are required, along with experience in large-scale ML systems on AWS.
Full description
We are hiring a Senior Data Scientist to join our team at Klivvr.
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What you'll do:- Own a domain such as credit, risk, or growth end to end, setting the modeling strategy and being accountable for the systems that result. - Take on the most ambiguous, highest-stakes problems, including framing what should be built and why before any modeling begins. - Make and defend the hard technical calls, choosing the simplest approach that solves the problem rather than the most sophisticated one. - Drive models into production and own their long-term health, performance, and reliability once they're live. - Set technical direction and standards that other data scientists build on, through design reviews, shared tooling, and engineering practices. - Mentor data scientists across levels and raise the quality bar for the team's work. - Translate business strategy into a coherent data science roadmap and communicate tradeoffs clearly to leadership.
To succeed in this role, you'll need to have:- 5+ years of hands-on data science or applied ML experience, with a track record of owning systems in production end to end. - Deep proficiency in Python (NumPy, pandas, scikit-learn) and SQL, and strong software engineering fundamentals. - Strong grounding in statistics, probability, and machine learning, with the judgment to know which method actually fits the problem. - Experience designing and operating large-scale ML systems on cloud platforms (AWS preferred). - A demonstrated ability to lead ambiguous, cross-functional initiatives without close guidance. - Excellent communication skills, including the ability to influence technical and business stakeholders and to make others better through your feedback.
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