Intuit Manager Data Science 

Kenya, Nairobi County, Nairobi 

311247997

• Lead a team of 3–5 Data Scientists to deliver high-impact product insights and models.
• Drive strategic decisions for the Payments ecosystem by uncovering trends, identifying opportunities, and translating data into recommendations.
• Define and track success metrics tied to business outcomes and customer impact.
• Build predictive models, segmentation frameworks, and advanced experimentation methods to inform product innovation.
• Partner with Product, Marketing, Engineering, and Analytics teams to influence roadmap and GTM strategies.
• Communicate complex findings clearly to technical and non-technical stakeholders.
• Champion a high-trust, data-driven team culture that values curiosity, experimentation, and continuous learning.
• Prioritize work for maximum impact, define decision-making frameworks, and remove barriers to execution.

The ideal candidate is a curious, proactive data scientist with experience in building scalable solutions, a strong understanding of customer behavior, and a passion for fintech.

• BS/MS in Statistics, Computer Science, Mathematics, or related fields.
• 6+ years in Data Science or Product Analytics, ideally in fintech or SMB-focused companies.
• 2+ years managing and mentoring Data Scientists or Analysts.
• Deep expertise in customer behavior analytics, predictive modeling, segmentation, and experimentation beyond A/B testing.
• Strong SQL and Python skills; familiarity with data visualization tools (e.g., Tableau, Qlik, Plotly Dash).
• Experience working cross-functionally in fast-paced, high-growth environments.
• Ability to build scalable, reusable analytics solutions; experience with AI tools is a plus.
• Excellent communication and stakeholder management skills.
• Familiarity with Git, command line tools, and general software development practices.

Preferred Additional Qualifications

• Fintech or SMB-focused product experience.
• Experience with growth analytics: feature adoption, customer health scoring, next best action models, etc.
• Exposure to Generative AI or multi-modal analytics for accelerating insight generation.