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Location:Tysons, VA (Hybrid) with some remote work·Work Authorization:EAD, Green Card or ·Work Type:Full Time Responsibilities include, but are not limited to: Gathering and cleaning HR data from various sources, such as HRIS, ATS, surveys, and external benchmarksPerforming descriptive, inferential, and predictive analysis using statistical methods and tools, such as Excel, SQL, R, Python, Power BI, Tableau, etc.
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Hands-on experience with other statistical programming or scripting languages (R, SPSS, Stata, Python, SQL). Master’s degree in Survey Research/Methods, Statistics, Biostatistics, Epidemiology, Public Health, Mathematics, Data Sciences, or other relevant statistical or social science field.
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Leverage a broad set of modern technologies - including Python, R, and Spark - to analyze and gain insights within large data sets. Advanced skill in Python and R. Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure Client (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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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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Technology Tools: AWS, Open Search and Python Data Science tools. Technologies to know: Statistical Tools may include: SAS, R, SPSS, Matlab, Mahout/MADlib, Stata. Conferences (recently attended by Praxis employees): AWS Summit, IoT World, Black Hat and DefCon. Training & Certifications: Splunk, AWS, Big Data/Cloudera, VMWare, Scrum Master.
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Significant experience programming in SAS, R, Python or other language. Support quarterly CECL process, managing data improvement and validation, and assisting CECL reserve determination preparation.
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Strong programming experience in Java and Python/R. Familiarity with SAS and with tools available in the AWS/Cloud environment. Develop, implement and test components using Java/Python/R of financial models, algorithms, cash flow simulations and pricing/risk metrics calculations in end-user or production computing systems for use in business decisions, financial and regulatory reporting and risk management.
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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. The environment involves Batch Pipelines involving core technologies such as Scala, Python, Spark, EMR, Glue, Airflow, Step Functions, Delta, Uniform Catalog, Iceberg, DynamoDB amongst many others.
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Develop robust data engineering pipelines utilizing Apache Nifi and Python to include use and development of REST APIs and microservices. Develop, deploy and provide feature enhancements using Python for data science products and services, to include Python packages, code documentation, notebooks, and microservices.
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Strong programming skills in Python, R, SQL, and React. Utilize programming languages such as Python, R, and SQL to develop and deploy NLP and AI models. As a Data Analytics Engineer, you will be responsible for designing, developing, and implementing natural language processing (NLP) and AI-based solutions to enhance our products and services.
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The Risk Data Science team is looking for a Data Scientist to develop advanced machine learning models, guide measurement, strategy, and data-driven decision making to support various risk and operational areas at SoFi. The Data Scientist will work closely with Risk, Product, Engineering, and Operations teams to design solutions for loss mitigation.
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NGEN-R SMIT is the largest IT services program for the Navy, by delivering the OCONUS Enterprise Network (ONE-Net); inclusive of cybersecurity services, network operations, service desk, and data transport.
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Proven e xperience in Python, Spark, Scala, or R, using open-source frameworks (for example, scikit learn, TensorFlow , Pytorch) Proven e xperience in Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
$110,000 - $220,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Proficiency in data integration through use of analytical tools such as GIS, Matlab, Python, R, etc., preferred. Experience with applied approaches for data and statistical analyses, modeling and/or product development of coastal dynamics and/or systems.
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Familiarity with software products associated with cyber system engineering for data analytics, including SQL security, TANIUM Endpoint Management Software, PowerShell, McAfee, App Blocker, and Splunk ITSI. Experience with software development environments and tools, including Linux, Python, C, Bash Scripting, Perl, SQL, Splunk Phantom, UBA, and UIPath.
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