Solve your business problems with data
In a world where Artificial Intelligence, Big Data, and Data Science became a purpose by themselves, we refocus attention on your business problems and use data as a tool to deliver immediate value.
What we do
Identify data-related business opportunities
Artificial Intelligence & Big Data won't add value without a clear strategy. We help you identify your challenges and data-driven solutions
Implement data-driven decision making
Decisions can be greatly improved by data. We help you build the culture and tools to unlock the full potential for your organization
We consulted our client on a high-level data strategy and developed a detailed roadmap through actual use cases.
After mapping out their goals and requirements, we designed their data warehouse, and first BI / ML applications.
We’re a mix of industry experts and researchers who fell in love with the intersection of business, math, and data. We’ve seen and solved most problems in the data (science) industry and have the technical background to solve any problem using cutting-edge methods (if necessary). But most importantly, we believe in prioritising impact above everything else.
Christina is a young and highly motivated data scientist with strong foundations in machine learning and classical statistics, economics, and econometrics. At ACMetric she translates business problems into quantitative research questions and delivers easily accessible, and action-oriented results.
Evgeniya is a data scientist with an academic background. She is a part of the DTAI research group at KU Leuven (Belgium), where she is doing research on Machine Learning and working on her PhD. Evgeniya also teaches at the Harbour.Space University (Spain, Thailand) and occasionally contributes to other educational projects. Rich teaching experience helped Evgeniya develop excellent communication skills and learn how to explain complex mathematical concepts to a non-technical audience.
Hande is an associate professor of econometrics and data science at the Vrije Universiteit Amsterdam. She has a PhD in econometrics and her research focuses on developing methods to analyze large data sets. Her research is published in top econometric journals. She is teaching at the Master of Econometrics and Operations Research program at Vrije Universiteit Amsterdam. Her academic position enables her to follow the developments in the methodology literature and their applications closely, which gives her an opportunity to apply the newest methods in ACMetric products.
Petr is a Postdoctoral fellow at IST Austria. He has strong foundations in statistics and machine learning and is a published mathematician. Petr obtained his PhD at Columbia University in New York.
Martijn is a young and ambitious Engineer with a background in Aerospace Engineering at the TU Delft. He has extensive experience in research and consultancy. For ACMetric, he defines key metrics and uses machine intelligence to extract important information hidden in the data.
Marc is a data scientist with 5+ years of experience and part time assistant professor in econometrics and data science at the Vrije universiteit. For ACMetric he has worked on the methodology and production of various projects such as dynamic pricing and markdown optimisation. Marc obtained his PhD in econometrics at the Vrije Universiteit.
Paolo is associate professor in econometrics and data science at the Vrije Universiteit Amsterdam. He holds two PhD's in statistics and publishes his research in the top journals in the field. His academic career keeps him informed of all the latest data science techniques, ensuring ACMetric products are at the forefront in the industry.
Artem is a lead data scientist with 10+ years of experience. While at ACMetric he has lead projects for Adidas and Sberbank. Before that he solved data science problems for companies in different industries such as BAM and the city of Amsterdam. Artem obtained his PhD in econometrics at the University of Maastricht.
Christian runs the Driver Growth & Compliance Data Science teams at Uber directly impacting the experience of +3m active drivers. His teams face a wide range of challenges from designing metrics & measuring impact via A/B tests over building economic models to machine learning algorithms for, e.g., document classification and churn prediction. He also holds a PhD in Game Theory from Maastricht University.