Enterprise Data Scientist

This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact.

At Kikoff, our Enterprise Data Scientists sit at the intersection of data, strategy, and partnerships. You will work closely with internal teams — including Business Development, Product, Engineering, and Data Engineering — as well as external partners to drive mutual value through rigorous data analysis. Your work will directly inform how Kikoff grows and optimizes its partnership ecosystem, identifying new opportunities and deepening existing relationships.

• →Partnership analytics: Own the analytical framework for measuring and improving the performance of existing partnerships. Develop metrics, build dashboards, and deliver actionable insights that help both Kikoff and its partners maximize value from the relationship.
• →Partner development & EDA: Conduct exploratory data analysis to surface signals in data that identify new potential partners — understanding market fit, customer overlap, and opportunity sizing to help business development prioritize outreach.
• →Strategic influence: Translate complex analyses into clear, compelling narratives for both internal stakeholders and external partners. Serve as a data-driven voice in partner conversations and business reviews.
• →Analytical rigor: Develop and test hypotheses using a robust toolkit — including statistical modeling, regression, segmentation, and causal inference — to evaluate partnership performance and guide strategic decisions.
• →Cross-functional collaboration: Partner closely with Business Development, Product, and Operations to align on goals, define success metrics, and ensure data integrity across the partnership lifecycle.

• Bachelor's degree or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or a related field
• 4+ years of experience in analytics, preferably with exposure to partnerships, business development, or B2B enterprise contexts
• Expert proficiency in SQL
• Solid understanding of statistical analysis, experimentation design, and common ML techniques
• Demonstrated ability to communicate data findings clearly to both technical and non-technical audiences, including external stakeholders
• Collaborative, intellectually curious, and comfortable navigating ambiguity in a fast-moving environment