Data Scientist

• 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

Benefits

• Flexible Paid Time Off
• Social Events – summer party/holiday party, etc
• 401k
• Medical & Dental coverage 100% paid premiums for employee
• Paid Parental Leave
• Long Term Disability
• Kochava Academy – Corporate Training & Development- Expertise writing high-performance SQL queries and working with large-scale datasets
• 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
• 3+ years of hands-on Data Science experience. A formal degree is not required if you have equivalent knowledge gained from experience
• Collaborative mindset with the ability to work across teams, balance competing requirements, and influence peers constructively
• Strong proficiency in Python for statistical programming and machine learning development
• Experience working with data visualization tools and communicating analytical findings clearly to non-technical stakeholders
• Solid understanding of a broad range of statistical methods and machine learning algorithms
• Strong sense of ownership — you document your work thoroughly, validate it rigorously, and ensure quality at every step
• Experience with MLOps practices, model monitoring, or automated reporting pipelines
• Track record of improving team workflows, data documentation practices, or analytical infrastructure
• Familiarity with experimental design and A/B testing frameworks
• Experience mentoring junior data scientists or contributing to onboarding and training programs
• Experience classifying, storing, and handling data in accordance with data governance policies
• Experience with distributed computing and big data technologies such as Apache Spark
• Experience with data visualization tools such as Tableau
• Experience working with high volume and high velocity data in a distributed environment
• Experience working with cloud data warehouses such as Amazon Redshift or Google BigQuery