Data Scientist, Kochava

• 3+ years of hands-on Data Science experience. A formal degree is not required if you have equivalent knowledge gained from experience
• Strong proficiency in Python for statistical programming and machine learning development
• Expertise writing high-performance SQL queries and working with large-scale datasets
• Solid understanding of a broad range of statistical methods and machine learning algorithms
• Demonstrated ability to independently deliver end-to-end model development — from problem definition through production deployment
• Ability to build solutions that are pragmatic, consider business constraints, and can be maintained and extended by others
• Experience working with data visualization tools and communicating analytical findings clearly to non-technical stakeholders
• Strong sense of ownership — you document your work thoroughly, validate it rigorously, and ensure quality at every step
• Collaborative mindset with the ability to work across teams, balance competing requirements, and influence peers constructively

Desirable

• Design, build, and deploy production-grade machine learning models and analytical solutions that are robust, scalable, and maintainable by other data scientists
• Apply a broad range of statistical methods and ML algorithms, using sound judgment on when — and when not — to use them
• Write highly performant, well-documented, and reproducible code in Python and SQL
• Collaborate with product managers, business stakeholders, and engineering teams to clarify requirements, scope analytical work, and deliver on project milestones
• Make thoughtful trade-offs between model performance and interpretability, complexity and simplicity, and computational cost and accuracy
• Identify and resolve data quality issues and analytical gaps; drive improvements to data science workflows and model reliability
• Actively contribute to model reviews, experimental design discussions, team planning, and post-deployment performance evaluations
• Work to find and address root causes of model performance issues, leaving systems better than you found them
• Contribute to on-call support and take ownership of issues, driving resolutions or ensuring clear handoffs
• Automate manual reporting tasks and contribute to operational excellence across the team
• Mentor junior data scientists and actively participate in the hiring and interview process