About the role

Data Scientist optimizing payments ecosystem for Preply, enhancing user experience through data-driven insights. Collaborating with teams to improve payment processes and fraud management.

Responsibilities

Develop a deep understanding of the Payment Operations dynamics of our product, including user behavior and the economics of Preply’s marketplace.
Analyze data related to payment processes, including pay-ins and pay-outs, to uncover insights and identify opportunities for optimization.
Monitor transaction performance to detect and troubleshoot anomalies in payment flows (e.g., failed transactions, latency issues, fraud patterns).
Lead systematic analysis of fraud and risk patterns, including regular review, cleaning, and optimization of existing risk rules, and the development of data-driven, smart rules that go beyond static or manual blocks.
Act as a key data partner to ML Platform and AI teams, bridging Product, Payouts, and Payment Operations with advanced analytics and modeling capabilities, ensuring data science fully complements product and operational ownership in payments and fraud.
Quantify and model the impact of new product features and initiatives, identifying growth opportunities and contributing to the prioritization of our product roadmap.
Help define key performance indicators, tracking events, and engagement metrics that align with business goals and product improvements.
Design, execute, and evaluate large-scale experiments to test new ideas and measure their effectiveness in driving business outcomes.
Build strong relationships with data and technical leaders to foster collaboration and drive cross-team initiatives.

At least 4 years of experience in fraud management and payment operations analytics, including ML‑based fraud systems, pattern analysis, rule management, and product optimization through experimentation.
Experience designing and analyzing A/B tests with a strong grasp of relevant statistical concepts.
Strong understanding of data analysis concepts such as conversion, LTV, cohort analysis, retention, etc.
Proficiency in one or more programming languages (e.g., SQL, Python), with the ability to write efficient and scalable code.
Experience with advanced statistical modeling, predictive analytics or machine learning.
Curiosity, problem-solving and critical-thinking skills, as well as the ability to proactively identify and address challenges.
Ability to craft compelling stories with data and communicate complex insights in a clear and engaging way, driving change among diverse stakeholders.
Interest in the bigger picture, feeling excited to impact the product roadmap and strategy.

An open, collaborative, dynamic, and diverse culture;
A generous monthly allowance for lessons on Preply.com, Learning & Development budget, and time off for your self-development;
A competitive financial package with equity, leave allowance, and health insurance;
Access to free mental health support platforms;
The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries (and counting!)