Senior Data Scientist
On-site One Kattameya Full-time Senior Data Science
At a glance
Senior Data Science role at Klivvr. One Kattameya · full-time.
Pay not stated Data Scientist salary
RoleData Science
SenioritySenior
LocationOne Kattameya
WorkplaceOn-site
EmploymentFull-time
PostedJun 8, 2026 · 4mo ago
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Take charge of a domain such as credit, risk or growth, from modeling choices through the systems they produce
- Define unclear, high-impact problems before modeling, including deciding what needs to be built and why
- Choose practical technical approaches, then explain and stand behind those decisions
- Put models into production and remain accountable for their performance and reliability over time
- Set shared technical practices, mentor data scientists and connect business strategy to a roadmap for the team
What you bring
- At least five years in hands-on data science or applied machine learning, with production systems owned end to end
- Strong Python and SQL skills, alongside sound software engineering fundamentals
- A solid command of statistics, probability and machine learning, with judgment about which methods fit
- Experience building and running large-scale machine learning systems on cloud platforms
Who this fits
This senior role suits someone who can lead ambiguous work independently, guide other data scientists and communicate tradeoffs to technical and business leaders. The position is onsite at One Kattameya.
From the employer
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.
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