or apply directly on Kikoff's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 17 days Kikoff's roles stay open a median of 69 days
- Reposted
- No
- Salary listed
- No 9% of Kikoff's roles list one
- Ghost-job risk at Kikoff
- high 37 stale, 0 reposted of 54 open
- Hiring momentum
- 73 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-24
Measured from postings appearing on and disappearing from Kikoff's own greenhouse board since 2026-08-03. Full hiring picture for Kikoff.
About this role
As a Senior Data Scientist at Kikoff, you will lead data initiatives for core credit-building products, collaborating closely with product, engineering, design, and marketing teams. Your responsibilities include defining metrics, overseeing product experimentation, and evaluating AI-driven models, while also contributing to the overall data science best practices within the organization. You will play a key role in shaping the data strategy and ensuring that insights drive product decisions and improvements.
- benefits
- 1/5
- freshness
- 5/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Kikoff as an employer.
What you need
- Experience partnering with product, engineering, and marketing peers across the whole arc of the work: strategy, goal setting, approach, and execution, not just the analysis at the end.
- A track record of defining metrics from scratch and getting a team to run on them, including for products where success was hard to pin down.
- Designed and ran experimentation programs, including changes where clean randomization wasn't available. Comfortable with quasi-experimental and causal inference methods, and clear about their limits.
- Hands-on with production-quality SQL and Python. You build pipelines, analyses, and models yourself.
- Experience building or working closely with models that drive decisions in a product, in any domain: ranking, fraud, forecasting, personalization, underwriting, detection, LLM applications. We care about the judgment, not the vertical.
- AI tools are a core part of your daily analytical work and you can show how they changed the speed and quality of what you ship.
Nice to have
- Built or ran an evaluation program for an LLM-based product: judge design, validation against human labels, test-case construction from real failures.
- Consumer fintech experience, especially products that expand access for un- and under-banked customers.
- Built an experimentation or causal inference practice in an org that didn't have one.
- Have taken a model from proof of concept to production, or shipped test and challenger models that changed a product decision.
- Have mentored, onboarded, or managed the work of other data scientists.
Worth weighing
- No specific benefits or perks mentioned in the posting.
- The role involves significant collaboration across multiple teams, which may require strong interpersonal skills.
- The focus on AI tools suggests a modern approach to data analysis, but also implies a need for adaptability as workflows evolve.
Summarised from Kikoff's posting. Read the full original.
Listed by Kikoff on their greenhouse job board, last confirmed open on 2026-10-24. PitchMeAI is not the employer.
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