Michael Brener

Principal Data Analyst @Self-employed

✔️ IT🧑‍🔬 Engineer🧨 ConsultingQuantitative Analyst🏦 FinanceProduct ManagerProject ManagerLife CoachingBusiness AnalystData AnalystBI Analyst

Michael Brener is a Principal Data Analyst who is currently self-employed. He has an extensive background in data analysis, utilizing his skills to help businesses make informed decisions based on data-driven insights. Michael specializes in transforming raw data into meaningful information, using various statistical tools and software. His expertise includes data modeling, data mining, and predictive analytics. As a self-employed professional, he offers customized data analysis services to meet the unique needs of each client. His ability to interpret complex data using SQL in combination with BI tools and present it in an understandable manner makes him a valuable asset for businesses looking to leverage data for strategic decision-making.

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Work Background

Brener Coaching and ConsultingHead of Risk Management

Aug. 2023Vilnius, Vilniaus, Lithuania · Hybrid* Freelance Risk, AML and Customer Underwriting consultant, FinTech sector * Since Dec. 2023 - Heading Risk Management program at Libernetix, Riga

UNIPaaSRegional Managing Director

Sep. 2022 - Jul. 2023Vilnius, Vilniaus, Lithuania · Hybrid* Lead an application of EMI licensing with Bank of Lithuania, permanent board member of the LT subsidiary * Managed and successfully executed the transition of the UK company (sister entity) to the automated and scalable customer onboarding and ML monitoring flow * Supervised all risk controls of the organisation

IntuitRisk Solutions Lead

Nov. 2014 - Sep. 2022Center District, Israel · Hybrid* I was leading a dozen of strategic risk programs of the organisation with stakeholders from different teams across the globe * My flagman program was Graph Database and Link Analysis technology implementation. This program was recognised as one of the biggest technological jumps of the organisation and was one of the main drivers of bunch of large-scale supervised ML models with very strong performance * I was leading the design of multiple monitoring dashboards for risk KPI's, extensively using sophisticated SQL scripting and Tableau visualisation tools