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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Collaborate with cross-functional teams including data scientists and product managers to align machine learning solutions with business objectives.
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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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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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Expertise with CI/CD processes and contributes to a sustainable and robust codebaseExperience with batch jobs/data pipelines and is comfortable deploying through these systems (i.e. Airflow, Luigi, Composer)Build and interact with production systems for serving machine learning predictions.
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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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Job DescriptionGen AI Solution Architect/Delivery Lead -DescriptionJob Title: Databricks Generative AI Solution Architect / Delivery LeadJob Location: Hybrid (preferred base cities: Atlanta, NYC, Chicago, NYC, Dallas, Houston, and Seattle)Job description: The AI Architect will leverage expertise in data science, specifically in artificial intelligence, machine learning, and software architecture to address complex business challenges.
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Additional experience with Pyspark, AWS S3, Lambda, EC2/AZ, Data bricks, Machine learning (ML), GenAI/ Computer Vision, Theory of Probability, GitLab, R Programming, GCP & Airflow will be preferred.
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Experience With Machine Learning Libraries and Frameworks (TensorFlow, MLlib, Pandas, Numpy) is an added advantage. Title: Senior Data Engineer - Big Data. Experience in the areas of design and implementation of Ratings Data Ingestion pipelines with modern AWS cloud and other technologies such as S3, Hive, Databricks, Scala, Python and Spark.
$77,400 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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Position Summary: The Senior Manager of Data Analytics predominately uses a tech stack of Power BI, SQL, Visual Studio Code, Snowflake, and Excel to answer questions to data that is ETL’d from our ERP, CRM, and various internal and external data sources.
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Day to day you’ll be building governed datasets to feed analytical reports and data science models, optimizing and creating new ETL pipelines, or building data models in Looker. Experience with data transformation orchestration tools like dbt or Dataform.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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Ability to migrate the Data Science models written on native python language to the multi node Databricks compute. Role DescriptionWe are currently seeking a talented and motivated senior Azure Data Engineer to join our Risk Technology Team. The role will be responsible for developing, deploying solutions for risk, regulatory, compliance projects on Azure platform and be at the forefront of on-prem to cloud migration initiative.
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Deep knowledge in Machine Learning, Deep Learning, Data Mining, Information Retrieval, Statistics. Machine Learning Scientist – Quant AI - Vice PresidentThe Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.
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Understanding of strengths and weaknesses in application of Machine Learning and Artificial intelligence to applications in Transaction monitoring and Sanctions screening. Senior Director, Model Validation - Compliance ModelsCountry: United States of AmericaThe Senior.
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data science machine learning senior manager jobs Title: science in Manhattan, NY
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