Business Data Scientist, gTech Users and Products

• Translate ambiguous business and operational challenges into scalable investigative solutions, models, and actionable insights.
• Lead project work and mentor team members in designing and deploying data science models, ML/AI solutions, robust data pipelines, and evaluation frameworks.
• Build and implement reusable, scalable investigative tools and automated solutions that optimize the operational processes.
• Collaborate with engineering partners to write robust code and implement tools that improve troubleshooting efficiency, operational workflows, and the end-user experience.
• Manage cross-functional stakeholder expectations, communicating complex technical findings and data insights clearly to both technical and non-technical audiences to drive business decisions.

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
  
• Experience with Machine Learning (ML) models or Artificial Intelligence (AI).

Preferred qualifications:

• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
  
• Experience applying ML models and AI techniques to analyze complex datasets and solve business problems.
• Strong foundation in statistical methodologies to analyze operational data and validate business decisions.
• Ability to manage multiple projects with engaging priorities in an ambiguous environment.
• Ability to translate complex data insights into compelling narratives to influence cross-functional partners and executives.

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
  
• Experience with Machine Learning (ML) models or Artificial Intelligence (AI).