Lead Data Scientist

Description

Job Description:

Our client is seeking a passionate, data-savvy Lead Data Scientist to join the Analytics team and fuel our mission of growth through data-driven insights and opportunity discovery. In this dynamic role, you will dive into our customer, product, channel, and digital data to uncover opportunities for consumer experience optimization and customer value delivery. You will also enable stakeholders with actionable, intuitive performance insights that provide the business with direction for growth. The ideal candidate will have a robust mix of technical and communication skills, with a passion for optimization, data storytelling, and data visualization. You will collaborate with a centralized team of analysts as well as teams across the organization, including Product, Marketing, Data, and senior leadership. This is an exciting opportunity to be a key influencer in the company's strategic decisions and to learn and grow with our Analytics team.

Responsibilities:

• Synthesize data from our analytics tools into actionable insights about customer and prospect behavior, digital sales and servicing performance, and customer value delivery. Clearly communicate these recommendations to internal stakeholders and senior leadership.
• Actively participate in cross-functional initiatives, collaborating with team members to achieve and measure project success. Provide opportunity analysis, measurement plans, dashboards, and post-release/testing analyses.
• Ability to quickly grasp complex technical concepts and make them easily understandable through various communication mediums like visualizations and presentations.
• Extract and analyze data using analytics tools such as Python, R, and/or SAS.
• Create compelling, intuitive dashboards to enable the business with critical metrics, with a focus on data automation, anomaly detection, and actionable data visualizations.
• Partner with Digital, Marketing, Product, and IT partners to evaluate the success of new initiatives.
• Collaborate with Fraud and Risk partners to identify and mitigate threats to Huntington assets.
• Apply visualization techniques to internal and external data sources to make accurate and actionable analyses in a timely fashion.
• Be a partner in the building of KPIs and metrics that help to gauge the health and success of our digital and Omni assets and initiatives.
• Create self-service dashboards for internal business partners to learn, understand, have access to, and derive insights from data, metrics, and KPIs.
• Apply automation techniques to manual processes to create efficiency, improve accuracy, and build upon successes that create a suite of self-service assets.

Requirements

Required Technical Skills:

• Business intelligence and data mining tools Tableau and Tableau Server.
• Tableau/SQL experience is a MUST!
• Cloud/Snowflake experience is a plus (Need to at least be familiar).
• No Java or C++ is needed.
• Candidate must be a good speaker - Half the time spent building and a good portion spent interacting with other people.
• Direct experience with SQL programming and large database applications such as Oracle, DB2, SQL Server, SPSS, Teradata, and Hadoop.

Basic Qualifications:

• Master's degree in Computer Science or Information Systems, Decision Sciences, Statistics, Operations Research, Applied Mathematics, Engineering, or a STEM degree.
• In lieu of a master's degree, a bachelor's degree with a minimum of 3 years' work experience in analytics or data science.
• Experience partnering with someone on another team and overseeing a group of OFFSHORE candidates.

Preferred Qualifications:

• Developing and applying statistical or machine learning methods in a corporate environment through applications such as R, Python, or SAS.
• Extensive experience with programming languages R or Python.
• Programming languages Java or C++ in a data mining context.
• Building web-based applications using HTML, CSS, Perl, and JavaScript.
• Experience with web analytics tools and implementation - Adobe Analytics (formerly Omniture SiteCatalyst), Google Analytics, IBM Digital Analytics (formerly Coremetrics), Webtrends.
• A/B testing tools (Optimizely, Adobe Target, etc.) and effective test design (establishing sample sizes, statistical significance measurement, etc.).

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