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Healthcare Data Scientist Jobs
Company | Smart TechLink Solutions Inc. |
Address | Washington, United States |
Employment type | CONTRACTOR |
Salary | |
Expires | 2023-09-01 |
Posted at | 9 months ago |
Responsibilities:
• Should have the ability to communicate data insights to all organizational levels, concluding, defining recommended actions, and reporting results across stakeholders.
• Should work on integrating data from different data sources.
• Should be working on pre-processing large datasets to build machine learning models, automating, deploying, and maintaining them into production.
• Should be able to understand how the deployed models run correctly.
•Should develop, test, and deploy data structures using Entity-Relationship Diagramming, and data modeling tools.
Requirements:
• 5+ years of experience in data science specialization, including statistical data analysis.
• Expertise in Linear/integration optimization, simulation, and game theory. Must be an expert and specialized in optimization and game theory.
• Deep understanding of common database technologies, such as SQL Database/Server, SQL Data Warehouse, Oracle, DB2, Netezza, MySQL, and other data sources.
• Experience working with distributed computing tools (Hadoop, Hive, Spark, etc.)
•Experience with Tableau is a plus.
• Experience with large scale data mining tools such as Spark
• Advanced understanding of best practices for structuring and organizing Data Lake file systems for large volumes of data.
• Experience performing advanced data pipelines, data structure and modeling, data processing, data extraction, joining, manipulation cleaning, analysis, and presentation for medium to large datasets.
• Experience developing models for forecasting, classification, clustering, regression analysis, recommendations, variable selections, and natural language processing.
• Strong grasp of experimental design, A/B testing, and advanced statistical analysis
- • Experience leading end-to-end data science project implementation including training, testing, and deploying machine learning models in production environments.
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