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Utilize programming languages like Java, Python, SQL, Ruby and Go, Container Orchestration services including Docker and Kubernetes, CM tools including Ansible and Terraform, and a variety of AWS tools and services.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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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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Frameworks & Tools: Extensive experience with Hibernate/JPA, AWS, Databricks, Angular/React JS, and JBOSS Enterprise SOA. Knowledge of Apache Kafka, Apache Spark, and ActiveMQ is a plus.
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Lead and participate in solutioning sessions, working hand-in-hand with businesses/clients, translating business objectives into actionable machine learning/data science use casesWhat You'll Bring.
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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer Sunnyvale, California, United States. The Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipelines based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle issues or provide recommendations for the next step of solving problems.
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What you will be responsible forDevelop/ Build and enhance data pipelines using Python, Spark based data engineering solutions (Databricks), and SQL (AWS Redshift). Hands on development in Python, PL/SQL, SQL, Shell Scripting, AutoSys. Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
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Proficient in programming languages such as Python, Scala, or SQL. In-depth knowledge of Apache Spark and its ecosystem. Hands-on experience with the Databricks platform and Apache Spark.
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Strong proficiency in programming (e.g., SQL, Python, R, MATLAB), database technologies (Oracle, mySQL, relational databases; graph databases are a plus), machine learning/deep learning (network architectures are a plus), dimensionality reduction techniques (e.g., PCA), and possible cheminformatics software suites.
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4+ experience with coding and scripting (Python, SQL, Java, JavaScript, Golang, Bash, Perl or Ruby) 4+ Experience with technologies Apache Mesos, Marathon, or Apache Spark.
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Experience in Data Engineering leveraging AWS Redshift, S3, Glue, Airflow, Python, SQL and Kubernetes. AWS, Redshift, Apache Airflow, Glue, Python, Informatica, Snowflake, IICS, ERP, Client.
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Required background/ Skillsets: Prior working experience in Data bricks Snowflake Python Data science background Proficiency in Python for software development and scripting. Experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with machine learning concepts and frameworks is a plus.
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KEY QUALIFICATIONS: Python, SQL Data processing, ML experience Data Warehouse knowledge ETL pipeline knowledge Data Engineering Data Science Data Analytics, Data Mining PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: Kubernetes, Tableau, PowerBi MongoDB Microsoft Cloud Services like Azure and AKS Snowflake SQL Server data platform Software development (including design, implementation, testing, and change management.
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Full Stack Development experience, including experience with Python, Django web applications, REACT web applications or other Javascript frameworks, RESTful API architecture, and incorporating machine learning models into web apps.
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C#, C, Java, Ruby, HTML5, XML, SQL, Perl, Python, Ajax, Qt) on Windows, Linux, mobile platforms, and embedded real time operating systems (VxWorks, Linux, QNX, Integrity, Windows CE, and others for Motorola, Intel, TI, and custom processor designs.
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