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University of Rochester Rochester Data Science Consortium - Data Scientist - 219340 in Rochester, New York

Rochester Data Science Consortium - Data Scientist

Job ID

219340

Location

The College

Full/Part Time

Full-Time

Favorite Job

Regular/Temporary

Regular

Opening

Full Time 40 hours Grade 054 Data Science Consortium

Schedule

9 AM-5 PM

Responsibilities

Position Summary:

The University of Rochester’s Goergen Institute of Data Sciences (GIDS) is seeking Research Analysts for its new Rochester Data Science Consortium (RDSC). This role will be responsible for scoping, planning, leading, and executing multiple projects in collaboration with our industry partners. The University actively pursues a broad spectrum of Data Science research in diverse areas such as Artificial Intelligence, Cognitive Sciences, and business and marketing analytics, as well as the methods, tools, and infrastructure required to sustain leadership in the field.

As a member of GIDS/RDSC, the successful candidate will have responsibility for projects in the RDSC, which is focused on advancing regional economic development and supports a range of partnerships with industry in areas of data science research, training, technology development and access to research computing expertise and resources. The candidate will work with the GIDS/RDSC Director and university researchers in these domains to understand both current world-class competencies and planned future research thrusts. Deep collaboration is required with the region’s commercial entities, from pre-startups to small businesses to Rochester’s traditional core industrial and manufacturing base. The role will require hands-on interactions with these stakeholders, and partnering with University faculty and students to successfully scope and deliver projects in a timely fashion.

Analytics have shown the power to dramatically transform all aspects of our lives – Big Data is no longer an issue, rather it is how, when everything has become a data source, we best leverage and capture the meaning of this data. Our goal is to leverage the power of UR Data Sciences to transform regional businesses beyond their existing core offerings to forward-looking, high-value, transformative offerings that propel a redefinition of Rochester as a dynamic economic hub.

Responsibilities:

  • Work with RDSC and University technical staff to provide innovative, scalable and viable solutions involving data processing and analysis using advanced techniques in statistical modeling and machine learning

  • Understand and solve research problems across technical domains of relevance including business and marketing analytics

  • Maintain broad knowledge of UR and URMC research in the areas of statistical modeling and machine learning

  • Assess commercialization potential for emerging research in relevant areas

  • Keep abreast of trends related to statistical modeling and machine learning by self-studying, attending seminars, courses and conferences.

Qualifications:

Bachelor's degree in related discipline such as Computer Science, Business, Mathematics, Statistics, Science or Engineering; and 3-4 years of related experience, preferably 1-2 years in a supervisory capacity; or an equivalent combination of education and experience. Master's degree preferred.

Preferred Qualifications

The ideal candidate will be a self-starter with a proven ability to continually learn new things in a fast-paced environment. The successful candidate will have a MSc some level of industrial experience in a relevant field (Data Science, Computer Science, Engineering, Imaging, etc.). Excellent oral and written communication skills are a must. Experience in the following areas preferred:

  • Research

  • Client and customer-facing experience

  • Data analytics in applied business and retail contexts

  • Statistical modeling including time series analysis, spatial models, regression models

  • Machine learning algorithms including LASSO, random forests, gradient boosting machines

  • Scripting languages including Python and R using data visualization and machine learning libraries

How To Apply

All applicants must apply online.

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