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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Strong experience with Python/R, forecasting methodologies, machine learning and statistics, Build collaborative relationships with key stakeholders; set priorities aligned to business goals; communicate analysis, strategies, timelines, and work of the data science & machine learning team, and gain buy-in from executive leadership.
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Job Description Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities.
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Expert in SQL, capable in Python, and experience with Business Intelligence tools such as Looker, Mode Analytics or Tableau. Lead Machine Learning Engineer. Working with our business operations, finance, sales, marketing, product, and insurance teams to design and build data sets to drive Vouch’s business.
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3 to 5 years of hands-on development experience in Machine Learning System. Experience as a Machine Learning engineer building feature engineering pipelines, deploying AI models, and optimizing model inference.
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As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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Support GDIT’s FedCiv business areas by developing solutions to deliver capabilities, including Data Science and Machine Learning. Programming:Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala.
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Design, build, and deploy data engineering pipelines that extracts, transforms raw data into analytics base tables to support downstream machine learning models using languages such as Python, R and SQL.
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In this role, you will support government customers within the Department of Defense (DoD) on various projects to develop solutions incorporating technologies such as machine learning, artificial intelligence (ML/AI), robotic process automation (RPA), and cloud infrastructure.
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Hands on experience working on analytical platforms like SAS, R, Python, Azure ML. Extensive experience with data engineering technologies, business intelligence tools, designing, reporting and delivering analytic solutions, data management and warehousing, and the strategic use of information.
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Provide hands-on ML engineering to develop and customize machine learning algorithms (as a research code) in Python for achieving end results. The Data Scientist will conduct artificial intelligence and machine learning (AI/ML) research and development for a portfolio of NASA applications with focus on aeronautics projects such as Air Traffic Management, Aviation Safety, Sustainable Aviation, and/or Advanced Air Mobility.
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Specific tasks will include data curation and database expansion, database management, website and data server maintenance, data archiving, working with Stanford libraries, and creating computational tools such as Python scripts for data processing to support artificial intelligence and machine learning efforts in cardiovascular imaging and modeling.
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Or, alternatively, Bachelor’s degree (or foreign education equivalent) in Engineering, Statistics, DataScience or a related field plus three (3) years of experience as a Data Analyst or a relatedoccupation performing advanced analytics using predictive modeling and machine learning.
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Scientific background in life sciences or engineering and demonstrated expertise in one or more of the following areas: data analytics, data visualization, statistics, machine learning, predictive modeling, decision analysis under uncertainty, artificial intelligence, Python and/or R, app development, and Tableau dashboard development.
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The team uses emerging technologies and methods such as data fabric, machine learning, GenAI, NLP, computer vision, artificial intelligence automation, big data analytics, and cloud native application development to drive innovation, operational efficiency, and provide the data product excellence our customers have come to value and trust us for.
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