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Minimum RequirementsBachelor's degree in business administration, computer science, mathematics/statistics, engineering, management information science, data processing or related field and experience with Tableau, Cognos/Argos, SQL, and/or SAS is required.
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Experience with a data scripting language (Python, SAS, R) & SQL and analyzing large and complex data sets is required. Bachelor’s degree in quantitative fields such as Statistics/Data Science/Econometrics/Mathematics/ Business Analytics preferred.
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Typically, Minimum 4 Years Relevant Exp Demonstrated experience with sophisticated analytics tools and programming languages (e.g., SAS, SPSS, R, Python, SQL, HiveQL, Spark, Hadoop) Proficiency with visualization platforms such as Tableau, Qlikview, PowerBI, D3, or JavaScript.
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Writing SAS programs using SAS/BASE, SAS/MACRO, SAS/GRAPH, SAS/STAT, and SAS/SQL to map raw clinical data to CDISC compliant datasets and create tables, figures, and listings reporting results of clinical trials for investigational medications.
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Experience with analytical / statistical programming tools for data extraction and summarization, statistics, visualization and analysis (Alteryx, SAS, SQL, R, Tableau, etc. Consulting Research Analyst would have a BA/BS degree in social science, public health, economics, statistics, actuarial science or equivalent related field and a minimum of 5 years of related work experience or equivalent combination of education and experience.
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BA/BS degree in Computer Science, Information Systems or equivalent practical experience in business intelligence, data analytics, data science or data engineering roles.
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5 years of experience must include: Data analytics and statistical analysis of financial risk data; Policy and regulatory analysis; Data analytics tools including: R, Excel, and PL/SQL; Anti-Money Laundering (AML) and Know Your Client (KYC) guidelines; Oracle and relational databases; and User Acceptance Testing (UAT) and defect management.
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Demonstrated proficiency in one or more of the following computing languages: SQL, SAS, R, Python, C, JavaScript. 3+ years of relevant work experience in health insurance, healthcare, public health, pharmacy, advanced analytics, machine learning, data science OR a master's degree in one of the fields listed above OR an actuarial credential.
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Access, query, aggregate, manipulate, consolidate, and summarize omni-channel customer and visitor data from multiple large-scale data sources using data science tools (SQL,R, Python, SAS, Microsoft Power BI, Azure, Adobe, Databricks.
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Additional Requirements: Knowledge, Skills, and Abilities (KSAs): Data Integration; SAS Tools; SQL/SAS; Web Report Studio; Written Communication; Data Extraction; Data Mining; Data Visualization Tools; Statistical Programming Language; Relational Database Management; Project Management; Business Planning.
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SAS, SQL, Python, C, VB.net, Java, JavaScript or R), relational databases (e.g. Teradata, Oracle) or visualizations tools (e.g. PowerBI, Tableau, Spotfire) SAS, SQL, Python, C, VB.net, Java, JavaScript or R), relational databases (e.g. Teradata, Oracle) or visualizations tools (e.g. PowerBI, Tableau, Spotfire.
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Programming languages may include—but are not limited to—SAS, Python, R, SQL, Java, or MATLAB. Proficiency in programming languages such as SAS, Python, SQL or Unix. Coursework or work experience applying predictive modeling techniques from finance, statistics, mathematics, data science, or computer programming to large data sets.
$114,000 - $170,000 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Advanced degree (Masters with 4+ years of experience or PhD) or Bachelor's degree with 6+ years of experience in data science, bioinformatics, biostatistics, epidemiology, immunology, public health, or related fields.
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Experience or familiarity with some of the following tools: programming languages (e.g., Python, SQL, PHP, SAS, R, MATLAB, Java, C. Facilitates collaboration between staff engaged in similar work and with similar interests across the Division Basic Qualifications: Strong internal technical stature and demonstrated technical depth in modeling and analysis, with BS in a quantitative field such as Data Science, Operations Research, Computer Science, Mathematics, Statistics, or other related technical discipline.
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Familiarity with some of the following technologies and disciplines: SQL, SPSS, Spark, R, SAS, Python, NoSQL, Hadoop, Scala, Java, Hive, Windows, Linux, computer hardware, cloud systems, and architecture, Ruby on rails, shell script, Visio, Android/iOS, Agile and DevOps tools such as GIT or JIRA, RESTful and Microservice APIs, SDLC, JavaScript, MS Visual Studio, security fundamentals, OWASP, UNIX, C.
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