Finn Dignan

Senior Analytics Engineer at Datatonic

Finn Dignan has a diverse work experience in the field of data analysis. Currently working as a Business Intelligence Analyst at Datatonic since August 2022. Prior to that, Finn worked as a Research Analyst - Data at Imperial College London from September 2021 to October 2022. Before that, Finn worked as a Data Analyst at the Natural History Museum from January 2021 to September 2021.

Finn's earlier roles include working as a Data Analyst at Domestic and General Insurance from April 2019 to January 2021, focusing on service measurement and implementing data automation processes. Finn also worked as a Market Risk Analyst at Motability Operations Ltd from February 2018 to October 2018, where they forecasted the market for used cars and ensured accurate data processing.

Finn's career started as an Insight and Reporting Analyst at Kantar TNS from February 2017 to February 2018, where they processed and monitored data streams, prepared reports, and automated reporting processes. Prior to that, Finn worked as an Insight Analyst at CACI International Inc from June 2015 to February 2017, assisting clients with marketing and location planning using GIS-based solutions.

Overall, Finn Dignan has gained extensive experience in data analysis, reporting, automation, and market forecasting throughout their career.

Finn Dignan completed a BSc degree in Economics from Birkbeck, University of London, from the years 2013 to 2017. Later, in the years 2018 to 2019, they pursued an MSc degree in Economic History from The London School of Economics and Political Science (LSE).

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London, United Kingdom

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Datatonic

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Datatonic, 4 x Google Cloud Partner of the Year, helps leading companies make better business decisions with the power of Modern Data Stack and MLOps. We work with clients to deepen their understanding of consumers, increase competitive advantages, and unlock operational efficiencies by building a solid cloud foundation and accelerating high-impactanalytics and machine learning use cases. Our team specialise on Google Cloud Platform, share a passion for data, and believe in a pragmatic approach to solving hard problems.


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51-200

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