Phd In Statistics Jobs in Ohio (NOW HIRING)

Description Summary: The Lead Data Scientist contributes to building and developing the organization's data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision-making processes. Duties and Responsibilities: Performs advanced analytics methods to extract value from business data. 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. Determines requirements that will be used to train and evolve deep learning models and algorithms. Articulates a vision and roadmap for the exploitation of data as a valued corporate asset.

Influences product teams through presentation of data-based recommendations. Evangelizes best practices to analytics and products teams. Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring.

Performs other duties as assigned. Basic Qualifications: Master's degree in computer science, statistics, economics or related field 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, including experience with big data analysis tools and techniques, and building and deploying predictive models, web scraping, and scalable data pipelines. Preferred Qualifications: PhD in computer science, statistics, economics or related fields Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling Strong experience with R, RSTudio, Python, SAS, SQL, NoSL 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 #LI-NG1 #LI-Onsite 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.

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