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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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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. 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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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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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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Integrating Databricks with other AWS products such as SNS, SQS, and MSK.What we are looking for: Bachelor's or master's degree in computer science, Information Technology, or a related field. Strong technical proficiency to contribute to data engineering task in an AWS and Databricks ecosystem.
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We are a premier IT consulting firm specializing in delivering top-tier Data Science solutions to companies across various sectors such as. 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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Partner with a whole range of teams within the Data organization (Analytics, Data Science, Data Engineering, Data Architecture, Data Quality & Governance, Program Management) to deliver high impact, efficient Data solutions.
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8+ years of experience in data engineering or full-stack quantitative analytics/data science roles. Drive the adoption of agile methodologies and DevOps practices to ensure efficient and high-quality data engineering processes.
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Ability to migrate the Data Science models written on native python language to the multi node Databricks compute. Qualifications and Skills IT professional experience in Azure Cloud with over 5+ years of Azure Development Ability to recreate existing legacy application logic and functionality into Azure Databricks/Data Lake, SQL Database and SQL Datawarehouse environment.
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Has expert knowledge of standard data science and statistical techniquesHas expert knowledge of two of causal inference techniques, Gen AI (LLM) implementation, or contextual banditsExperience implementing scalable systems (Google Cloud preferred.
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A Baccalaureate Degree from an accredited college or university with a major in Computer Science, Systems Engineering, applied Mathematics, Business Administration, Economics/Statistics, Telecommunications, Data Communications, or a related field of study; and.
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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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Collaborate across multidisciplinary teams—Compliance, Data Science, Model Risk Management, Data Governance, and Human Resources. This position reports to the Head of Fair Lending and works closely with the Head of Data Science, Fair Lending Compliance, and Model Risk Management to establish and lead a comprehensive and robust Fair Lending Analytics function.
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VP, Portfolio Management Data Science. Will lead initiatives to enhance processes and infrastructure, leading the implementation of data science initiatives, applying expertise in develop monitoring reports, dashboards, and predictive models to enhance risk assessment capabilities.
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A masters degree from an accredited college or university in one of the following areas of study: environmental or chemical engineering, limnology, environmental science, marine science, geology, biology, earth science, chemistry, physics, or health science; or 2.
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data science jobs Title: high school teacher in New York, NY
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