Senior Data Scientist

Summary

Join FairMoney, a leading mobile banking institution, as a Data Scientist to develop data science-driven algorithms and applications. You will improve business processes like risk and debt collection, optimizing credit services for clients. This role requires strong analytical skills, experience with machine learning algorithms, and proficiency in Python and SQL. You will work with stakeholders to identify opportunities for leveraging data, mine and analyze data from various sources, and develop processes to monitor model performance. FairMoney offers competitive benefits including paid time off, family leave, training and development budget, paid company business trips, and flexible remote work options.

Requirements

• Strong background in Mathematics / Statistics / Econometrics / Computer science or related field
• 5+ years of work experience in analytics, data mining, and predictive data modelling, preferably in the fintech domain
• Being best friends with Python and SQL
• Hands-on experience in handling large volumes of tabular data
• Strong analytical skills: ability to make sense out of a variety of data and its relation/applicability to a specific business problem
• Feeling confident working with key Machine learning algorithms (GBM, XG-Boost, Random Forest, Logistic regression)
• Being at home building and deploying models around credit risk, debt collection, fraud, and growth
• Track record of designing, executing and interpreting A/B tests in business environment
• Strong focus on business impact and experience driving it end-to-end using data science applications
• Strong communication skills
• Being passionate about all things data

Responsibilities

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
• Mine and analyze data from company databases and external data sources to drive optimization and improvement of risk strategies, product development, marketing techniques, and other business decisions
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Use predictive modelling to increase and optimize customer experiences, revenue generation, and other business outcomes
• Coordinate with different functional teams to make the best use of developed data science applications
• Develop processes and tools to monitor and analyze model performance and data quality
• Apply advanced statistical and data mining techniques in order to derive patterns from the data
• Own data science projects end-to-end and proactively drive improvements in both data

Benefits

• Paid Time Off (25 days Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)
• Training & Development budget
• Paid company business trips (not mandatory)
• Contract: permanent or B2B
• Location: any, within 3 hours difference from CET
• Remote work: any combination of remote / office work is acceptable