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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, Python, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Candidates should demonstrate expert knowledge in one or more of the following areas: data management, machine learning, deep learning, artificial intelligence, data visualization, programming Python, programming in R, databases, and related topics, either through a record of teaching excellence or through industrial experience.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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As a Python Engineer at HRT, you’ll have an incredible opportunity to work in cutting-edge distributed compute environments at one of the top algorithmic trading companies in the world. At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech.
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Advertising and Media Consumption Analytics - With our purchase of Warner Media, AT&T is now a global media and entertainment leader, with exciting opportunities for data science applications that model consumer media consumption, develop personalized content, and optimize advertising effectiveness and delivery.
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Strong Dashboarding skills - have experience in data visualization on tools like Tableau, Spotfire, QlikView, Qlik Sense, Alteryx and Power BI. Transformation #Data Visualization #Tableau #Big4 #Consulting - BFSI #Data Analytics #Analytics #Project Management.
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Proficiency in data visualization tools: R, Python, Tableau, or similar. Act as a subject matter expert in marketing measurement science, specifically MMM + MTA unified-model measurement and media KPIs.
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Create trading applications and services for use by the Municipal Bonds Trading Desk using Java, TypeScript, SQL/Oracle, Python. Work in a Trading environment as part of an agile team doing hands-on full-stack development with emphasis on Java, TypeScript, Oracle and Python.
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Academic background in a science field (e.g., molecular biology, genomics, cell biology, immunology, biochemistry) and should have basic understanding of economics, macroeconomic factors, and government policy.
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Undergraduate teaching experience in core topics in Data Science such as programming, data mining, data visualization, Parallel and Distributed Computing, Machine Learning, Big Data Engineering and, Probability and Statistics will be considered an asset.
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Projects may include data transformation, data visualization, data digitization, artificial intelligence (such as LLM’s, NLP, & Gen AI) and various other initiatives. Possess strong technical acumen with an advanced understanding of one or more “no-code / low-code” digital tools such as Alteryx or Tableau and/or familiarity with one or more programming languages such as SQL or Python.
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Develop APIs & Batch Processing with technologies such as Python, Flask, Java, Spring, MSSQL, Snowflake in an Azure infrastructure. Solid hands-on experience in Python or Java and CI / CD tools (e.g., Github, Docker, Jenkins.
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Front end development experience (e.g. JavaScript, Angular, React, Vue.js) Familiarity with GenAI, NLP (Natural Language Processing) Experience in deploying cloud native applications to a cloud infrastructure (AWS, Azure, Google Cloud.
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Provide military science instruction and training and field instruction and training in accordance with Cadet Command's program of Instruction (POI), syllabus, and other ROTC-directed or emerging training in various settings on and off campus, to include field environments.
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Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques. Collaborating closely with various subject matter experts across various fields, our team leverages advanced statistical analysis, machine learning techniques, and data visualization tools to uncover patterns, trends, and correlations within the data.
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