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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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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Expert ability in operations research and statistical methods and techniques, including deployment analysis and resource allocation modeling, systems/operations analysis, simulation and optimization (linear and nonlinear, predictive analytics (e.g. deep learning, econometrics, time series/forecasting, vehicle routing, and related skills.
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RNN) in a work setting, not just academic projects Hands-on experience in building and deploying machine learning and statistical models using Python, PySpark, Machine Learning libraries, SQL. Experience in computing/programming skills; proficiency in Python, R, and Linux shell script.
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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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Experience: At least 5 years of experience in a business intelligence or data analytics role, with 2+ years in a leadership or management role Skills: Strong analytical and problem-solving skills Broad experience with data manipulation and analysis (SQL and e.g. Python, R, etc.
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Python Quant Developer - Risk Platform - London/New YorkSalary: Up to 200k base + bonus Location: New York or London Summary One of the world's largest hedge funds using innovative and cutting-edge technology, where data is fundamental to the investment process.
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SummaryOXMAN is seeking a Landscape Architect to join an all-star interdisciplinary team of deep thinkers and brilliant makers, leveraging data-driven approaches to ecology and landscape design with the goal of mediating between human-made and Nature-grown environments.
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You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics. You must be proficient in Python image processing (e.g., Pillow, OpenCV, scikit-image, and ITK.
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Python or related language- Experience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
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Strong knowledge of data science tools, ML frameworks and algorithms, and programming languages such as Python, R, SQL, and experience with cloud platforms (AWS and/or Azure) We are seeking a seasoned Data Scientist with deep LLM experience who will play a critical role in developing advanced predictive models and generative AI applications in order to transform the healthcare consumer experience and drive improved health outcomes.
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Experience gathering GPS data with Trimble GPS hardware and software and data processing with GPS Pathfinder Office software. Develop and deploy field GPS and data collection systems including Trimble GPS and Esri mobile applications.
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Required Skills: A senior delivery manager with 10+ years of relevant experience in the definition, analysis, implementation of data management related initiatives Financial service industry acumen and experience to lead large cross-functional initiatives in information architecture, reference models management and data integrations Deep understanding of data architecture principles, database technologies (SQL and NoSQL), data integration, BI and ETL processes.
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Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques. Extensive experience with, both traditional SQL and modern NoSQL data stores including SQL, and large-scale distributed systems such as Hadoop and or working in Snowflake/Databricks.
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Strong quantitative skills, prior experience with coding and data visualization tools such as Python, Alteryx, SQL & Tableau. Monitor stress, performance, liquidity, and counterparty risk metrics against the thresholds and perform deep-dive risk analysis on the outliers.
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