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Manipulating large data sets, data mining, and structuring of raw data using open sources tools such as SQL, Python, AWS, and Databricks to formulate or recognize patterns to generate new information and unlock information and insights that help the organization drive decision making.
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Utilize programming languages like Scala, Java, Python, SQL and GO and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. You will be working with Scala, Morphir IR, Go, Python, AWS (Fargate, EMR, Glue, S3), Cassandra, DynamoDB, Snowflake etc., and will have great opportunities to learn and contribute to the success of the platform.
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Proficiency in the use of analytical, statistical and econometric software packages such as STATA, Eviews, R, TSP, SPSS, Matlab and SAS.Preferred:Experience working with finance, budget, people analytics, macroeconomic data and writing macroeconomic research reports.
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Experience in data access tools, such as SAS, SQL, Python, and R. Knowledge of CMS claims data, including Medicare, Medicaid, and Marketplace, in the IDR or CCW environment with Fee-for-Service ( FFS ) , Medicare Advantage encounter data, Medicaid data in the Transformed Medicaid Statistical Information System ( T-MSIS ) , or Prescription Drug Event ( PDE ) data.
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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. 1+ years of data warehousing experience (Redshift or Snowflake.
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Support analytics team to execute data strategy and review analytic scripts (Python, Databricks, SQL, ACL). 1+ year(s) of experience in Excel, ACL, Python, SAS, Alteryx, R, SQL, or other advanced analytical programs.
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Proficiency with query languages such as Python, R, SQL, or SAS, mechanics, implementation, and impact modeling- Preferred. Exceptionally strong analytical abilities, with track record of identifying insights from quantitative and qualitative data- Required.
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Conduct or assess ad-hoc quantitative analyses, modeling, or programming using SAS, SQL, Python, and R. Also required are experience in quantitative analysis, model development and implementation using SAS, SQL, R, and Python.
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Key technologies include Python, SQL, Apache Spark, Azure, Data Warehousing, Lakehouse, Big Data, Relational Databases, Data Governance, and Data Quality. Essential skills and technologies for this role include Python, SQL, Apache Spark, Azure, Data Warehousing, Lakehouse, Big Data, Relational Databases, Data Governance, and Data Quality.
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In collaboration with the Chief Information Officer, Chief Information Security Officer, Chief Artificial Intelligence Officer, Senior Level professionals in analytics and AI, and other stakeholders, the CDO works to improve Agency processes based on insights derived from available data and effectively communicates the value and importance of data to executives and staff.
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3+ years in a hands-on role performing advanced predictive analytics using tools like Python, R, or Scala. Proficient understanding of relational (e.g. Oracle, SQL Server, PostgreSQL) and Big Data distributed structures (Hadoop/Spark) in order to source data effectively.
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High level of proficiency in Python, DataBricks, SQL, Spark, and other Data Engineering and DataScience tools. Desired Qualifications:- TS/SCI clearance is required- Minimum of 3 years of experience as a military Data Subject Matter Expert or related role, withdemonstrated experience with digital strategy, IT project management, enterprise architecture,SDLC (Software Development Life Cycle), or transformation.
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Demonstrated experience in conducting data research and development to integrate emerging technologies and techniques in data science and analysis such as analytics, machine learning, and cloud computing into organizational decision support systems and processes focused on transportation safety.
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Experience working in data analysis, modeling, and visualization packages in TensorFlow, Keras, PyTorch, Caffe, and Theano; and developing or integrating analytics in programming languages such as Python.
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Proficiency in programming languages such as Python, R, or Stata, and experience with data manipulation, analysis, and analysis libraries (e.g., SAS, SPSS, Power BI, MATLAB). Work with the data manager and/or data scientists to plan and build database infrastructure for each research study Experience with performing statistical analyses for clinical and field-based research studies (e.g., intervention studies, epidemiological studies, patient-reported outcomes research and/or clinical outcomes research, etc.
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