The Lead Data Science Consultant is responsible for being an advisor, practitioner and mentor for enterprise data science initiatives. Reporting to the Director of Analytics, the Lead Data Science Consultant will design and deploy data science capabilities to equip our clients with timely insights that fuel an exceptional client experience and ignites an innovative workplace. This senior role requires a blend of business acumen and technical skills to build ML models that inform strategic business decisions, product development and client experience innovations that lead to the improved operational and financial performance of our clients.   

The ideal candidate is client-focused and has a collaborative working style that fosters innovation within the organization, including strong analytical and storytelling skills, and technical aptitude. The individual will be required to think holistically as they work on complex problems with multiple groups and be able to provide actionable insights and informed decisions to our clients' executives.

Responsibilities:

• Prepare data, use statistics and machine learning to investigate problems with the goal of supporting the questions representing our greatest business needs;
• Develop and implement heuristics and statistical models to improve our business outcomes;
• Steer research activities that fuel innovation and continuous exploration using qualitative and quantitative analysis, leveraging operational data to define objectives, and testing hypotheses that influence product development;
• Use and promote data-exploration techniques to discover new or previously unasked questions;
• Manipulate and analyze complex, high dimensional data from a variety of sources using a multiple tools and data analysis techniques;
• Use data engineering skills and knowledge in various analytical programming languages and frameworks: Databricks, Spark, Python;
• Support our client's Chief Operating Office, Head of Enterprise Data & Analytics and Agile Portfolio Architects in effort to define, roadmap, and evangelize their data science practice;
• Work with Data Governance to design data-driven solutions based on data principles and policies.