Management Financial Group (MFG) is a holding organization, uniting leading providers of non-bank financial services in Central and Eastern Europe. MFG manages a rich portfolio of successful business models in the field of consumer loans, loans for micro and small businesses, credit cards, digital businesses and other alternative financial products and services. MFG brings together companies with different experience, history and traditions. Some of the institutions in the structure of MFG are in the initial stage of their development, some are rapidly developing and growing, others are well established in their industry with over 16 years of experience. More than 8 300 employees and associates in nearly 450 offices in Bulgaria, Ukraine, Romania, Poland, North Macedonia, and Spain take care of our customers every day.

In order to keep up with the growing holding portfolio and business diversity we have an opening for a Senior Data Scientist to join our Credit Risk and Revenue Optimization team.

What you would be able to do: Develop, test and deploy reinforcement learning, supervised and unsupervised machine learning and artificial intelligence models Possibility to work in diverse modelling domains – credit risk, churn prediction, segmentation, sales optimization, collection optimization Develop state-of-the-art predictive models with no restrictions to the possible modelling techniques used and participate actively in their deployment to production environment Possibility to practice and further develop the skills needed during the full machine learning project lifecycle – problem definition, data gathering, data wrangling, model development, validation, deployment and monitoring Develop and use fully automated systems for model and business monitoring Develop and use instruments to enhance productive work – project management through Kanban, software package development for repetitive tasks, automated model documentation and result presentation frameworks Communicate and present results to C-level stakeholders across different businesses Possibility to make decisions and have direct impact on the operations and financial results of the businesses Possibility to mentor junior and mid-level team members to develop people management skills Possibility for promotion to Data Science Team Leader Requirements: University degree or equivalent standard with a high numeric content: data science, artificial intelligence, statistics, mathematics, econometrics, business administration/ economics, finance, etc.; 4+ years of experience in the analytics field – machine learning models development Advanced in at least one programming language used for machine learning – R or Python Advanced user of relational databases – Microsoft SQL or equivalent Experience with data visualization tools – Power BI or equivalent Ability to work comfortably and combine data coming from a variety of data sources – relational and non-relational databases, csv and excel files, xml and json files Willingness to both learn and share knowledge with their colleagues Experience with project management is a plus Benefits: Opportunity to work, develop and grow in a dynamic environment, targeted at international expansion; Induction, ongoing training and development programme; Friendly and casual work environment; A team of people with extensive experience in the field and international acknowledgements; Competitive remuneration; Option for Multisport card at a discount price; Additional health insurance; Food vouchers; Smart mobile phone and sponsored mobile plan. We are searching for candidates who have the capabilities and are willing to develop into full-stack data scientists to help and support our diverse business operations with machine learning and artificial intelligence. If you enjoy making decisions, want your work to be recognized and important, and have the skills to bring business value through data science this role might be the best fit for you.

We encourage you to take a couple of minutes to submit your resume to be considered as the newest member of our professional team.

We appreciate and thank you for your application. Only short-listed candidates will be contacted.