Overview
On Site
Full Time
Skills
Banking
Customer Support
Visualization
Analytical Skill
Research
Deep Learning
Artificial Intelligence
Analytics
Sourcing
Presentations
Leadership
Coaching
Mentorship
Data Analysis
Predictive Modelling
Unstructured Data
FOCUS
Cloud Computing
Amazon SageMaker
TensorFlow
scikit-learn
Data Science
R
RStudio
Python
SAS
Database Architecture
SQL
NoSQL
Financial Services
Machine Learning (ML)
Scripting
Big Data
Web Scraping
Linear Regression
Modeling
Computer Science
Statistics
Economics
Network
Recruiting
SOW
Job Details
Description
Our Enterprise Data and Analytics team is growing. We're looking for a Lead Data Scientist to assist with building and developing our Data Science team and lead us into the next generation of banking. We are reimagining how data is used across the bank to better serve our customers, support our communities, and make our colleagues lives better. Our goal is to be the best performing Regional Bank in America, and we need data and analytics to meet that goal.
As we advance our data science and analytics capabilities, we want a Lead Data Scientist to develop experts in modeling complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. We are looking for a leader who has a passion for developing others, driving change, and continuously improving and evolving the application of technologies to meet todays and tomorrow's challenges.
Responsibilities:
Prioritizes analytical projects based on business value and technological readiness
Performs large-scale experimentation and build data-driven models to answer business questions
Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence
Evangelizes best practices to analytics and products teams
Acts as the go-to resource for machine learning across a range of business needs
Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring
Provides leadership, coaching, and mentoring to team members and develops the team to work with all areas of the organization
Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs
Anticipates and analyzes trends in technology while assessing the emerging technology's impact(s)
Coaches' individuals through change and serves as a role model
Skills:
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
Willingness and ability to learn new technologies on the job
Demonstrated ability to communicate complex results to technical and non-technical audiences
Strategic, intellectually curious thinker with focus on outcomes
Professional image with the ability to form relationships across functions
Ability to train more junior analysts regarding day-to-day activities, as necessary
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)
Financial Services background preferred
Basic Qualifications:
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
Preferred Qualifications:
Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling
Education:
Master's degree or PhD in computer science, statistics, economics or related fields
Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)
Yes
Workplace Type:
Office
Our Approach to Office Workplace Type
Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.
Huntington is an Equal Opportunity Employer.
Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.
Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.
Our Enterprise Data and Analytics team is growing. We're looking for a Lead Data Scientist to assist with building and developing our Data Science team and lead us into the next generation of banking. We are reimagining how data is used across the bank to better serve our customers, support our communities, and make our colleagues lives better. Our goal is to be the best performing Regional Bank in America, and we need data and analytics to meet that goal.
As we advance our data science and analytics capabilities, we want a Lead Data Scientist to develop experts in modeling complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. We are looking for a leader who has a passion for developing others, driving change, and continuously improving and evolving the application of technologies to meet todays and tomorrow's challenges.
Responsibilities:
Prioritizes analytical projects based on business value and technological readiness
Performs large-scale experimentation and build data-driven models to answer business questions
Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence
Evangelizes best practices to analytics and products teams
Acts as the go-to resource for machine learning across a range of business needs
Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring
Provides leadership, coaching, and mentoring to team members and develops the team to work with all areas of the organization
Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs
Anticipates and analyzes trends in technology while assessing the emerging technology's impact(s)
Coaches' individuals through change and serves as a role model
Skills:
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
Willingness and ability to learn new technologies on the job
Demonstrated ability to communicate complex results to technical and non-technical audiences
Strategic, intellectually curious thinker with focus on outcomes
Professional image with the ability to form relationships across functions
Ability to train more junior analysts regarding day-to-day activities, as necessary
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)
Financial Services background preferred
Basic Qualifications:
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
Preferred Qualifications:
Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling
Education:
Master's degree or PhD in computer science, statistics, economics or related fields
Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)
Yes
Workplace Type:
Office
Our Approach to Office Workplace Type
Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.
Huntington is an Equal Opportunity Employer.
Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.
Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.