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Data Scientist
Ref No.: 18-28811
Location: Raleigh, North Carolina
Start Date: 05/16/2018
Requisition Number ERS-/ERS-/2018/846786
Designation/Position Name Data Scientist
Number of Vacancies 1
Mode of Hire (TP/FTE/Either) Either
Customer Interview Required (Yes/No) Yes
Duration of the Project 6 months (extendable)
Job Title Data Scientist: Data Analytics / Machine Learning

Job Description
(Define At least 6 points which candidate is supposed to do)
Do you want to uncover hidden insights from data and use those to drive decisions and influence behavior to create business value for our clients? If so, the Analytics Practice within the Conduent Technology innovation (CTI) organiation has an exciting opportunity for you. The CTI Analytics team works closely with Conduent business groups to address real world challenges such as the rising cost of healthcare, mobility in urban society and payment card fraud in financial welfare programs, using the power of Data Analytics. We adopt a multidisciplinary approach that combines techniques from diverse domains such as data mining and machine learning, statistical modeling, simuation, optimization and multimedia analysis, and use big data technologies to consolidate and analyze volumes of data from multiple sources in a scalable manner.

We are looking for data scientists to work on machine learning, data mining, and statistical modeling for predictive and prescriptive enterprise analytics. Successful candidates will be expected to investigate state of the art techniques in advanced machine learning and statistical modeling, and design, develop, and deploy state-of-art, scalable systems for innovative analytics applications in a set of industrial verticals (e.g. healthcare, transportation, customer care etc.). Applicants will be expected to work with a diverse set of data sources, such as time series data, spatial, graph data, semi-structured and unstructured data, and build statistical/machine-learning models in support of on-demand, real-time analytic services. The applicant should also have strong skills in explaining and interpreting the analytic models and outcomes in both research and application contexts.

Research, design and prototype robust and scalable models based on machine learning, data mining, and statistical modeling to answer key business problems
Build tools and support structures needed to analyze data, perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices
Work with development teams & business groups to ensure models can be implemented as part of a delivered solution replicable across many clients
Present findings to stakeholders to drive improvements and solutions from concept through to delivery
Keep abreast of the latest developments in the field by continuous learning and proactively champion promising new methods relevant to the problems at hand
Collaborate closely with university partners and other scientists and engineers in a multidisciplinary work environment