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Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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Develop Azure Databricks data engineering, AI, and machine learning tasks. Hands-on experience on unified data analytics platform with Azure Databricks, Databricks Workspace user interface, managing Notebooks, Delta Lake with Python.
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Object oriented Python programming and solid experience with machine learning libraries - Pandas, NumPy, Scikit-learn, TensorFlow, etc. Building technical infrastructure required for efficient Extraction, Transformation, and Loading (ETL) of data from a wide variety of data sources by leveraging, object-oriented/object function scripting languages such as Python.
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NVIDIA is looking to hire a Senior Distributed Acceleration Engineer to work on RAPIDS, a suite of open-source software libraries that accelerates end-to-end data science and analytics pipelines on GPUs. RAPIDS relies on NVIDIA CUDA for low-level compute optimization but exposes high-performance GPU computing through user-friendly Python interfaces.
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Experience building loan-level credit/prepayment models from data preparation, data analysis, and model estimation through deployment into productionExperience with generalized regression models as well as machine learning frameworksVery strong programming and software design skills (Python, C.
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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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This candidate should be proficient in using BI tools such as Tableau, in addition to experience with one or more modern technologies such as relational databases, AWS, Snowflake, Python, Databricks, Git, and Machine Learning.
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You will be responsible for building end-to-end machine learning solutions, implementing models in production, and working with various data frameworks and tools such as Python, Spark, and Databricks.
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Scope, prioritize, prototype and deliver AI projects to help solve key business problems for Discretionary Equity, spanning both on-premises and AWS environments, and leveraging technologies such as Kafka, Spark, Cloud warehouses, and Data Lakes, and using programming languages such as Java, Python, and SQL.
$300,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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AI - Machine Learning: R/Rstudio, SAS, LLMs, NLP, ASR, Graph learning. Programming languages: Python, Spark, Ansible scripts, SQL, Scala (optional), Kafka (optional), Flink (optional.
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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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Experience leading teams in data analytics and data visualization, including selecting and applying the appropriate analytical techniques for statistical analysis, predictive modeling, simulation, and machine learning.
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You'll get to work on a consumer-facing product that uses high TPS micro-services, large streaming data, bandit and neural-network based recommendation algorithms, batch and real-time serving ML models and much more As a Backend Java Software Engineer III at JPMorgan Chase within the Personalization and Insights team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way.
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You’ll form strong relationships and collaborate with engineers outside of your immediate team, designers, leaders, PMs, data scientists, and user researchers to both scale our product efforts and invest in each other’s learning, growth, and success.
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Within MAP, the Analytics team fulfills two primary functions: 1) Operations research to improve decision-making using big data and advanced analytical methods, including machine learning and artificial intelligence techniques, optimization algorithms, simulation and statistical analyses.
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