Research Analyst and Machine Learning Specialist

Job description

Position Type: Permanent Staff

Department: Kenan-Flagler Bus Sch - 330100

Appointment Type: EHRA Non-Faculty

Vacancy ID: NF0002796

Position Summary: Since 1985, the Frank Hawkins Kenan Institute of Private Enterprise has encouraged cooperative efforts among privately owned business, higher education and government. More than a think tank we find ways to connect people and organizations, create opportunities and resources, and accelerate the achievement of our partners. Core operating support from the William R. Kenan Jr., Fund - along with grants and outside contracts - allow us to pursue research and consulting in a non-partisan setting. As part of the top-ranked UNC Kenan-Flagler Business School, we have access to intellectual resources, global networks and partners around the world. Our seasoned scholars use these connections to apply their leading edge thinking to real-world challenges. The primary purpose of the Research Analyst and Machine Learning Specialist is researching new technologies such as machine learning and data analytics methods, implementing these new methods in software tools, and understanding how to apply them to solve theoretical and practical problems. A large portion of the work consists in creating new data models, working with equations and scientific models, setting up experimental designs and testing in a software environment, as well as writing papers describing those experiments and results achieved.

Application Deadline:

Education Requirements: -Bachelor's degree in Computer Science, Computer Information Systems, Computer Engineering, math, or Engineering or related technical degree from an appropriately accredited institution; or - Bachelor's degree and some computer coursework from an appropriately accredited institution and one year of experience in business application consulting or development; or - Associate's degree in Computer Programming and one year of experience in application consulting or development; or an equivalent combination of education and experience. - Journey level requires an additional one year of experience. - Advanced level requires an additional two years of experience. - Bachelor's degree is preferred.

Qualification and Experience: - Experience in implementing machine learning or related data science methods using R and Python; - Experience working with large data sets (data mining, data analytics, data manipulation and reporting); - Experience with designing and running simulation experiments; - Superior programming skills in Java, JavaScript, JQuery, and Python; - Superior knowledge of Windows Server 2012+; - Ability to write complex SQL queries (Select, Insert, Update, Delete, Nested selects, Case statements etc.); - Proficient with Microsoft SQL Server (Stored Procedures, Indexes, database administration); - Excellent analytical ability; - Detail oriented with an ability to handle multiple projects and priorities; - Self-starter with strong organizational skills - Strong communication, interpersonal and customer service skills; - Proficient in Excel, Access and PowerPoint; - Prefer experience with programming for web portals; experience with programming for mobile applications; knowledge of NOSQL and MongoDB databases; and practical experience coding in Node.js, PHP, and Objective-C a plus;

Equal Opportunity Employer: The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or status as a protected veteran.

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Special Instructions for Applicants: In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire.




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Job No:
Posted: 11/7/2017
Application Due: 1/22/2019
Work Type: