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Booz Allen's Digital Battlespace Team is seeking an experienced full-stack machine learning engineer to build innovative new applications and products in the defense market. 5+ years of experience in software development and machine learning delivering high quality, scalable, and maintainable solutions.
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Experience must include 6 months in each of the following: Tableau; Python (Jupyter Notebooks, Spyder); Python libraries: Pandas, Matplotlib, GeoPands, Shapely; EXCEL VBA; QGIS (Geographic Information System); Power BI; machine learning techniques (including exploration data analysis, sampling, decision trees, clustering, random forest, logistic regression; and SAS language (Base/Macro.
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Programming with SQL, Python and R. Knowledge, Skills and Abilities Develop (from scratch) machine learning and/or deep learning approaches and algorithms to solve clinical and business (including operations, supply chain, human resources, finance) problems.
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Training machine learning models through Cloud Services including Google Cloud Platform and Microsoft Azure. electrical engineering, java, machine learning, processor, python.
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Use data science and machine learning principles to develop effective predictive models using 3D data. 5+ years of experience with machine learning, statistical modeling, and optimization techniques.
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Keywords:Boston MA Jobs, Software Manager, UI, User Interface, JavaScript, React, Redux, HTML, CSS, Bootstrap, Java, PHP, Python, AWS, PaaS, SaaS, IaaS, AppSync, Lambda, Cognito, BeanStalk, CloudWatch, CloudMonitor, EC2, S3, VPC, SQL, MySQL, AWS-RDS, DynamoDB, AWS-Elastic Cache, ETL, Data Lakes, AI, Artificial Intelligence, ML, Machine Learning, Data Science, Agile, Waterfall, Work From Home, Remote, Massachusetts Recruiters, Information Technology Jobs, IT Jobs, Massachusetts Recruiting.
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5+ years of experience in data science or a related field Strong knowledge of statistical modeling and machine learning techniques, such as regression analysis, clustering, and neural networks Experience with data analysis tools, such as Python, R, or SQL, as well as experience using Azure data science technologies, such as Azure Data Factory, Azure Data bricks, and Azure Synapse Analytics.
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Deliver software features including full stack software development, machine learning, Artificial Intelligence, scripting and optimizing databases. Experience must include 6 months in each of the following: software testing; MySQL; Oracle SQL; Linux; Java; J2EE; JavaScript; ClearCase; Struts; Spring Boot; Python; HTML; and CSS.
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Converting unstructured or semi-structured data into structured datasets using natural language processing, machine learning, and other extraction tools. As a Senior Data Scientist, you will apply advanced statistical models, machine learning techniques, and big data analytics to solve complex problems in medical science, aiding in the development of groundbreaking treatments and healthcare solutions.
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Knowledge of broad reaching technology concepts including Artificial Intelligence (AI)/Machine Learning (ML) Working with end users to help educate them in SQL, Python, and/or R, preferably with Apache Spark.
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Experience working in a machine learning environment is a plus. The ideal candidate will be highly skilled in data analysis, SQL, and AWS, with a strong ability to communicate complex findings clearly and effectively.
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Expertise in applying statistical techniques, machine learning models, and data extraction tools to solve complex problems. Certifications in data science, machine learning, or related technologies.
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Experience with generative AI, natural language processing, and/or machine learning methods. They will perform data cleaning and automated scripts, analyze textual and numerical data, and may utilize various tools to deploy generative AI, natural language processing, and machine learning workflows.
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Strong command of programming languages such as R, Python, SQL, and tools for data management and analysis (e.g., Power Automate). The ideal candidate will have strong experience in data management, bioinformatics, and computational biology, as well as the ability to collaborate with interdisciplinary teams to translate data insights into actionable outcomes.
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Distinct experience in advanced probability, statistics, machine learning, big data processing, analytics, and pipelining using Spark is essential, as well as experience in deep learning, generative AI, LLMs, and NLP. This role involves developing data science solutions, mentoring and imparting knowledge about machine learning and data concepts and techniques, as well as driving adoption of standards, processes, and tools to achieve high operational efficiency.
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