Tom Halloran is an experienced Agile Business Analyst specializing in Data with a proven track record of working with a diverse range of clients such as Bupa, Audi, Government Digital Service, and Office for National Statistics. He has practical experience with Big data technologies like Spark, Hadoop, Flume, Kafka, algorithm development, and the '3 Vs,' which are velocity, volume, and variety. Tom's expertise extends to machine learning and data science, database design, data models, ETL, data transformation, data quality, data cleaning, and data testing.

Tom is a graduate of General Assembly's data science course and was even a teaching assistant on the course. Additionally, he was previously a junior data scientist at GDS. He possesses excellent analytical skills and is an Excel expert, along with being proficient in data analysis in Python and SQL. He is highly skilled at extracting and communicating insights.

Tom's proficiency in Agile software is impressive as he has experience in shaping new products, features, and MVPs, including wireframing, prototyping, gathering input from stakeholders, and assessing technical implications. He is also experienced in planning sprints, managing backlogs, prioritizing, gathering requirements, writing stories and acceptance criteria. He is a certified Scrum Master and comfortable running teams with agile practices like retrospectives, stand-ups, sprint planning, etc.

Tom is especially interested in greenfield initiatives that use data analytics to create new products, solutions or features. His areas of interest include FinTech and retail banking. He is a proactive, detail-oriented and passionate Agile Business Analyst who understands how to align clients' requirements with the Agile methodology.