Lead Data Scientist

About This Role

Lead Data Scientist to assist with building and developing the Data Science team at Huntington, reimagining how data is used across the bank to better serve customers and support communities. This role involves developing experts in modeling complex business problems, discovering business insights, and continuously improving the application of technologies.

Responsibilities

• Prioritize analytical projects based on business value and technological readiness
• Perform large-scale experimentation and build data-driven models to answer business questions
• Conduct research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence
• Evangelize best practices to analytics and products teams
• Act as the go-to resource for machine learning across a range of business needs
• Own the entire model development process, from identifying business requirements, data sourcing, model fitting, presenting results, and production scoring
• Provide leadership, coaching, and mentoring to team members and develop the team to work with all areas of the organization
• Work with stakeholders to ensure that business needs are clearly understood and that services meet those needs
• Anticipate and analyze trends in technology while assessing the emerging technology’s impact(s)
• Coach individuals through change and serve as a role model

Requirements

• Up-to-date knowledge of machine learning and data analytics tools and techniques
• Strong knowledge in predictive modeling methodology
• Experienced at leveraging both structured and unstructured data sources
• Demonstrated ability to communicate complex results to technical and non-technical audiences
• Proven ability to lead cross-functional teams
• Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)
• Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)
• Demonstrated Expertise with at least one Data Science environment (R/RStudio, Python, SAS) and at least one database architecture (SQL, NoSQL)
• Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling

Qualifications

• Master’s degree or PhD in computer science, statistics, economics or related fields
• Master’s degree and 5+ years of experience related work experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, scripting languages, and packages, experience with big data analysis tools and techniques, and experience building and deploying predictive models, web scraping, and scalable data pipelines

Nice to Have

• Financial Services background
• Exposure to AI intake, prioritization, and implementation

Skills

* Required skills

Benefits