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Data Engineering using GCP Technologies (BigQuery, DataProc, Dataflow, Composer, DataStream, etc) years of work experience as a Big Data Engineer. Bachelor's degree in Computer Science, Systems Engineering or equivalent experience.
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Bachelors degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field and minimum 8 years of related experience, of which at least 4 years of directly related data analytics, data science, predictive modeling, machine learning, statistical modeling experience OR advanced in the required fields and 4 years directly related data science, analytics experience.
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6) Perform data acquisition using JSon, SQL, ODBC, JScript, or API for big data extracts and use programming languages like R, Python, SQL,.net, Java or C. This leader will work hands on in design and implementation of business-critical data science solutions, will manage, develop, and mentor the data science team, and build and maintain strategic technological data science roadmap for APS. The successful candidate needs to have strong knowledge and experience in data science and Artificial Intelligence (AI), programming techniques and cloud technologies and excellent organizational and leadership skills.
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We seek an experienced Senior Big Data Engineer to lead and enhance our data engineering initiatives. 5+ years of hands-on experience in Big Data engineering with a strong focus on Impala, Spark, Scala, Hive, Hadoop, and associated technologies.
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Experience in Data science, machine learning, or optimization models Experience in Python, Spark, Scala, or R, using open source frameworks (for example: scikit learn, TensorFlow, Pytorch) You are knowledgeable of databases, data warehouse design, cloud storage, and ETL best practices.
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Software Engineering & DevOps:Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI.Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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Bachelor’s degree in Computer Science, Engineering, IT, MIS, or a related disciplineExpertise in Python, SQL, and RExpertise in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON Expertise in ETL concerning metadata management and data validation Expertise in Unix and Git Expertise in Automation tools (Autosys, Cron, Airflow, etc.
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Experience with ML frameworks such as scikit-learn and Big Data feature engineering for ML. Certifications in Tableau, Power BI, RStudio, Azure Data Engineering and Databricks ML.
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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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Our people extend into all industries we conduct work with our clients in the areas of; data science, data engineering, data strategy, intelligent process automation, data ecosystems, intelligent industry/IoT, enterprise management, customer-first marketing, and data partnerships/disruptors (such as SAP, Microsoft, Google, AWS, Snowflake, Oracle, Adobe, etc.
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Research in Computational Data Science and Engineering includes: big data and computational statistics, AI and Machine Learning, internet of things, large and complex systems, intelligent transportation and infrastructure systems, remote sensing, autonomous vehicles, virtual and augmented reality, e-commerce, image and video processing, scientific and interactive visualization, high-performance computing, scalable algorithms, bioinformatics, and multi-scale multi-physics engineering systems.
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Master's degree in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field.
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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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A minimum of 6+ years of data science/ops research experience preferably within the supply chain industry, demand planning, CPG industry and/or retail replenishment. These technologies may include artificial intelligence, machine learning, statistical techniques, mixed integer linear programs, reporting/big data analysis, dashboarding, data integration, and other heuristics/algorithms.
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Desired Background PhD in Computer Science, or similar fields Expertise in data visualization, human computer interaction, or big data analytic techniques Knowledge of statistics and machine learning Proficiency in data structures and algorithms Expertise in visualizing complex data in popular frameworks (such as ggplot, d3, matplotlib, plotly, bokeh, etc.
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big data science engineering jobs Company: Capitalg Management Company Llc
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