What we do?

We help our customers in business decision making by preparation, analysis and visualization of data.

We support our clients in the best use of data. We propose assistance in the field of sales, risk, frauds & collection processes modelling and all these fields, where data does matter. We offer support in new solutions development or validation of already applied solutions.

Our competencies enable us giving holistic support for our clients, beyond competencies in data analysis we have also wide experience in developing and verifying business processes and preparation of sales strategies.

How can we help you?

We feel the data and analyze business environment, we state a crucial questions, conclude on the grounds of data, visualize conclusions and work variants of answers out.

We implement and propose solutions concerning scoring and predictive models based on behavioral and applicant data. We add data available online, which is very informative in terms of customer behavior. We pay attention to the use of mobile data, because broad using of smartphones significantly changes behavior of clients in terms of embracing products and services.

Employing mobile data gives opportunities to get to know new characteristics describing a consumer. Thanks to it, models employing these characteristics may significantly enhance effectiveness of actions led by our clients and increase experience of people using their services. We notice special meaning of mobile data in financial and e-commerce sectors.

1. Data analysis

Research, verification and analysis of data. Discovering relationships and information hidden inside. Drawing preliminary conclusions on the grounds of this data.

2. Data cleaning and drilling

Proper preparation of data towards using it in modelling, as well as, extracting precious information, that can significantly influence optimal decision making.

3. Visualization

Graphical presentation of connections existing between factors. Technique for making decisions and setting up decision variants.

4. Model

Preparation of proper solutions, implementation of techniques allowing to build an algorithm that supports decisions making.

5. Choice

Developing variants of answers according to expectations of the client.

For whom?

Do you sell online?

Do you deliver financial services?

Do you work in services?

Would you like to increase sale?

Would you like to increase shopping basket size?

Would you like to better recommend products for your clients?

Would you like to better estimate risk of your clients?

Would you like to decrease customers’ attrition?

Would you like to grant a mercantile credit?



In short TOP #top

Positiveness In short TOP #top


Dominik Ogonowski

Graduate of Wrocław University of Science and Technology at the faculty of Computer Science & Management and partner programme at Michigan Technological University. Graduate of Strategic Leadership Academy at ICAN Institute in 2004. Great experience in fields of credit risk management, monitoring and collections. Dominik has made of and deployed models of Agile method of working. He has also practical knowledge of IFRS9 and AIRB standards.

Marcin Chlebus, PhD

Graduate of University of Warsaw at the faculty of Economic Sciences, where he defended his Ph. d. thesis as well (Department of Statistics and Econometrics at the faculty of Economic Sciences at University of Warsaw). He has made of and deployed many models assessing credit, market, operational and fraud risk. He has acquired experience when working in a consulting company and in his own business practice. In addition, he uses his statistical knowledge in medical research.

Marcin Bykowski

Graduate of Szczecin University of Technology at the faculty of Computer Science. He has gained experience in banking in the field of customer relationship menagement and management information. He is an expert in deploying CMS class systems and solutions of advanced analytics and its implementation in CRM process. He specialises in the use of analytics in decision engines and optimalisation of business processes. 


Magdalena Markiewicz

Master in International Business Relations at the Poznań University of Economics and Business and post-graduate studies in management at Warsaw School of Economics. Experienced banking sector manager and strategic consultant. Main areas of competence include: creation and execution of business development strategy, management of product offer and customer portfolios, change management, as well as leading organizational changes and improving business processes. 

Katarzyna Chyrowicz

Graduate of Computer Science and Econometrics at University of Warsaw, faculty of Economic Sciences. She gained professional experience in big data working in a top insurance company, where her main tasks were loss ratio and cross-sell analysis. During her studies, she learned a lot about quantitative methods, credit risk modelling and machine learning algorithms.

Marta Małek

Graduate of Computer Science and Econometrics at University of Warsaw, Faculty of Economic Sciences. Has background in the field of statistics, econometrics, data analysis and credit scoring modelling. She is passionate about issues connected with machine learning, implementation of algorithms in R and Python, as well as employing programming tools in analysis and modelling.


Data Juice Lab ul. Żurawia 6/12, p. 508 00-503 Warszawa phone: +48 667 949 282 e-mail: d.ogonowski@datajuicelab.com