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    Data Science Reporting Analyst in Columbus, OH - Central Point Partners

    Central Point Partners background
    Banking / Loans
    Description

    Title: Data Science Reporting Analyst / Business Analyst (IT): II (Intermediate)

    JobID #: 5979

    Company: Huntington National Bank

    Position Type: Contract (6 months with potential extensions)

    Location: Columbus, OH, United States

    Hybrid role (3 days onsite, 2 days remote in Bank's Columbus office location)

    Job Description

    This individual will support providing transparency and visibility to key data and analysis supporting the Value Management Office (VMO) and delivery teams. They will play a key role in helping define the metrics and measurement of overall delivery effectiveness and end to end flow of work. They will help define data capture requirements, analyze patterns and trends, synthesize information into dashboards or presentations that convey insights and recommendations through storytelling, while maintaining a balance between the big picture and mastery of details.

    The Team:

    The Value Management Office (VMO) is responsible for helping drive a value-focused transformation across Huntington. The VMO includes the following functions:

    Working in direct partnership with our Finance and Strategy team to mature to an outcome driven organization.

    Driving the adoption of agile practices and standards

    Supporting continuous prioritization of initiative in partnership with business partners

    Supporting value tracking, IT execution alignment, and delivery flow

    Driving the continued evolution of our operational processes, training, coaching and communications

    Providing visibility through the development of reporting and analysis

    Basic Qualifications:

    Master's degree in Decision Sciences, Statistics, Applied Mathematics, Engineering, Computer Science or Information Systems, Operations Research, or a STEM degree In lieu of a Master's Degree OR Bachelor's degree with a minimum of 3 years work experience in analytics or data science

    Preferred Qualifications:

    Understanding of IT project execution and delivery including agile delivery best practices, concepts and measure of success.

    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.

    Developing and applying statistical or machine learning methods in a corporate environment through applications such as R, Python, or SAS

    Business intelligence and data mining tools such as BusinessObjects, MicroStrategy, Tableau and Tableau Server, Alteryx, or SAS Enterprise Guide/Miner Programming languages Java or C++ in a data mining context

    Building web-based applications using HTML, CSS, Perl, and JavaScript

    Financial Services background

    Job Responsibilities:

    Work with stakeholders to ensure that needs are clearly understood and that services meet those needs.

    Synthesize data from our analytics tools into actionable insights. Clearly communicate these recommendations to internal stakeholders and senior leadership

    Actively participate in cross-functional initiatives, collaborating with team members to measure success.

    Ability to quickly grasp complex technical concepts and make them easily understandable through various communication mediums like visualizations and presentations.

    Create compelling, intuitive dashboards to enable the business with critical metrics, with a focus on data automation, anomaly detection, and actionable data visualizations.

    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 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.



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