What are the responsibilities and job description for the Data Scientist Indianapolis, IN (Must be local to Indiana) - 6+ Months with Potential extensions position at Jobs via Dice?
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Role: Data Scientist
Location: Indianapolis, IN
Duration: 6 Months with Potential extensions
Bachelor s Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics and 2 years of experience
Or a Master s Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics
or 4 years of experience and passion for leveraging data to drive significant organizational impact.
Exp w/Shiny, Dash, Flask,or Streamlit to build user-facing interfaces, connect to backend data pipelines, and deploy lightweight analytic applications
Experience connecting to backend data pipelines, and deploy lightweight analytic applications
Experience using (R, Python, SQL, etc.) to manipulate and draw insights from large data sets as well develop software for automation
Advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
Experience with data manipulation to include cleansing, standardizing, and transforming
Broad knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.)
Role: Data Scientist
Location: Indianapolis, IN
Duration: 6 Months with Potential extensions
- Must be local to Indiana ****
Bachelor s Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics and 2 years of experience
Or a Master s Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics
or 4 years of experience and passion for leveraging data to drive significant organizational impact.
Exp w/Shiny, Dash, Flask,or Streamlit to build user-facing interfaces, connect to backend data pipelines, and deploy lightweight analytic applications
Experience connecting to backend data pipelines, and deploy lightweight analytic applications
Experience using (R, Python, SQL, etc.) to manipulate and draw insights from large data sets as well develop software for automation
Advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
Experience with data manipulation to include cleansing, standardizing, and transforming
Broad knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.)