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James Kelleher has a strong background in data engineering and data science. In their current role as a Data Engineer at Helm, they are responsible for various tasks related to data processing. Previously, at Attentive, they worked as a Software Engineer II and was involved in creating jobs in Airflow and onboarding databases to AWS DMS. As a Data Engineer at CBRE Build, they focused on developing ETL pipelines and integrating Slack for reporting and error detection. At CraftJack, James worked as a Data Science Consultant, analyzing auction data and building models to improve profitability. At Prescriptive Data, they served as a Data Science Team Lead and Data Engineer, designing and implementing analytics infrastructure. Other positions held include roles at Conductor, Inc., PivotalPath, The Huffington Post, and the Courant Institute of Mathematical Sciences. Throughout their career, James has demonstrated proficiency in programming languages such as Python and Java, as well as using tools like Pandas, SQL, and Airflow.

James Kelleher has a Bachelor's Degree in Interdisciplinary Computer Science and Mathematics from the New York University Gallatin School of Individualized Study, which they obtained between 2010 and 2014.

James attended Newark Academy from 2003 to 2010, but there is no information available regarding the degree or field of study during that time.

James has also obtained several additional certifications. In 2015, they received a Coursera Verified Certificate in R Programming and completed The Data Scientist's Toolbox course. In 2016, they completed courses in Exploratory Data Analysis, Getting and Cleaning Data, Reproducible Research, Statistical Inference, and Regression Models, all leading to Coursera Course Certificates. In 2017, they obtained a Coursera Course Certificate for completing a course on Machine Learning.

In 2020, James obtained several certifications from Udemy, including Apache Spark with Scala - Hands On with Big Data!, Apache Airflow - The Hands-on Guide, and Spark And Python for Big Data with Pyspark.