Klivvr
FinTech
SeniorDataScientist
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Scientist at Klivvr. Skills: Data Science, Applied ML, ML Systems. Own a domain end to end. Set modeling strategy”
Industry & Context.
Problem solving
What They're Looking For.
Must Have
5+ years data science experience, 5+ years applied ML experience, Track record of owning systems in production, Proficiency in Python, Proficiency in SQL, Software engineering fundamentals, Grounding in statistics, Grounding in probability, Grounding in machine learning, Experience designing ML systems on cloud platforms, Experience operating ML systems on cloud platforms, Demonstrated ability to lead ambiguous initiatives, Demonstrated ability to lead cross-functional initiatives, Ability to lead without close guidance, Excellent communication skills
Nice to Have
AWS preferred for cloud platforms, Ability to influence technical stakeholders, Ability to influence business stakeholders, Ability to make others better through feedback
What You'll Do.
Own a domain end to end
Set modeling strategy
Be accountable for systems
Take on ambiguous problems
Take on high-stakes problems
Frame what should be built
Frame why it should be built
Make hard technical calls
Defend hard technical calls
Choose simplest approach
Drive models into production
Own long-term health of models
Own performance of models
Own reliability of models
Set technical direction
Set standards for data scientists
Mentor data scientists
Translate business strategy
Create data science roadmap
Communicate tradeoffs to leadership
How You'll Work.
Team & Collaboration
Cross-functional initiatives; With leadership
Communication Scope
Communicate tradeoffs
Full Job Description
## Description We are hiring a Senior Data Scientist to join our team at Klivvr. ## 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.
Applying for this Senior Data Scientist role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Lever
- Lever uses a streamlined one-page form — apply in under 5 minutes.
- LinkedIn import works well; review parsed data before submitting.
- The cover letter field is optional but visible to reviewers — use it to differentiate.
- Referral codes from employees can significantly boost visibility of your application.
ANONYMOUS · UNFILTERED
What do employees actually say about Klivvr?
Real rants from real employees. Read before you apply.