Data Scientist
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Data Scientist
Ref No.: 18-00260
Location: Central, New Jersey
Start Date / End Date: 01/15/2018 to 06/29/2018
The Department of Health is interested in hiring a qualified Data Scientist for its Prescription Overdose: Data-Driven Prevention Initiative (DDPI). The successful candidate ideally will have extensive experience working with large public health databases such as hospitalization data, vital records (death records) and prescription monitoring database. The Data Scientist will lead the preparation and consolidation of public health data to identify indicators for the dashboard and perform predictive modeling and analytics. The successful candidate will work closely with the Department’s Healthcare Quality and Informatics team assigned on this project, the Data Architect and Office of Information Technology Services (HIT) staff. Job responsibilities and duties • Research and develop statistical learning models for data analysis • Collaborate with HQI and HIT to understand general Department and the specific DDPI project needs and devise possible solutions • Keep up-to-date with latest technology trends • Communicate results and ideas to key staff in DOH • Implement new statistical or other mathematical methodologies as needed for specific models or analyses • Optimize joint development efforts through appropriate database use and project design  
Skills Required • Extensive background in data mining and statistical analysis • Ability to understand various data structures and common methods in data transformation • Excellent pattern recognition and predictive modeling skills • Experience with programming languages such as Java/Python is an asset • HDFS / Data Lake Stores / Analytics • SQL Databases / Warehouses / BISM Stack (SSMS, SSDT, SSIS, SSAS, SSRS) • Analysis Services (Tabular Mode / DAX / Cube concepts) • Experience with modeling and presentation technologies (SQL Server Analysis Services, Reporting Services, MicroStrategy, Business Objects, Cognos, Tableau, PowerBI, others) • Expertise in BI-related data architecture, integration, modeling, and presentation • Understands BI-related features and limitations of common database platforms (SQL Server, Analysis Services, Oracle, DB2, Postgres, others) • Experience with ETL technologies (SQL Server Integration Services, Data Factory)