Sr Data Scientist – Ria Money Transfer
Ria Money Transfer, a business segment of Euronet Worldwide, Inc. (NASDAQ: EEFT), delivers innovative financial services including fast, secure, and affordable global money transfers to millions of customers along with currency exchange, mobile top‑up, bill payment, and check cashing services. We offer a reliable omnichannel experience with over 600,000 locations in nearly 200 countries and territories, aiming to open ways for a better everyday life. We believe in creating a world where people can build the life they dream of, one customer, one family, one community at a time.
About This Position
We are seeking a Senior Data Scientist to join our Data Science team. You will play an integral part, providing analytical excellence that drives both Ria and XE’s strategy. At both Ria and XE, your contributions will be appreciated by millions of people worldwide. The ideal candidate is passionate about asking and answering questions in large and complex datasets, and can communicate that passion to business owners and staff.
Responsibilities
Develop and deploy machine learning models and statistical analyses to support business objectives.
Design and document end‑to‑end analytical workflows and process maps for scalable data science solutions.
Build decision engines and rule‑based systems to automate and optimize business decisions.
Define, monitor, and report on KPIs for ML products, ensuring alignment with business goals.
Create and maintain dashboards to visualize model performance, business impact and operational metrics.
Conduct exploratory data analysis, hypothesis testing and model validation.
Collaborate with product managers, engineers and business stakeholders to translate requirements into data‑driven solutions.
Mentor junior data scientists and contribute to best practices in experimentation, reproducibility and model governance.
Communicate findings and recommendations clearly to technical and non‑technical audiences.
Stay current with emerging trends and technologies in data science and AI.
Work on projects such as supervised and unsupervised model development.
Own analytical frameworks that guide the product roadmap.
Design rigorous experiments and interpret results to draw detailed and actionable conclusions.
Develop statistical models to extract trends, measure results, and predict future performance of our products and services.
Build simulations to project impact of various product and policy interventions.
Enable objective decision‑making across the company by democratizing data through dashboards and other analytical tools.
Use expertise in causal inference, machine learning, complex systems modeling, behavioural decision theory etc. to shape the future of Ria and Xe.
Present findings in a compelling way to influence leadership.
Support other projects as directed by more senior staff.
Requirements
Business acumen – understands key challenges facing our business and partners with key stakeholders to find creative ways to apply data science to solve them.
Analytical skills – identify, measure and impact the important metrics needed to manage and monitor data quality; able to simplify complex content.
Attention to detail – appropriately checks all work for errors and does not let important details slip when it comes to data and its accuracy.
Creative problem solving – able to use creativity and curiosity as tools to pick apart any problem, producing a solution which is relevant and realistic.
Efficiency – able to quickly iterate on data generation and refinement. Look for ways to improve processes to maximize efficiency and remove redundancy.
Proactivity – acts without being told what to do at each step; generates novel ideas and processes to drive the business and team forward.
Qualifications
Advanced Degree (MS, PhD or MBA) in quantitative fields such as Data Science, Computer Science, Statistics, Mathematics, Operations Research or Engineering.
Advanced experience developing Machine Learning models (supervised, unsupervised).
Knowledge of a variety of ML techniques (clustering, decision tree learning, neural networks etc.) and their real‑world advantages/drawbacks.
Strong programming skills in Python and PySpark, comfortable with Git and cloud environments such as AWS.
Experience in big‑data analytic environments/technologies (Hadoop, Spark).
Ability to write complex, efficient and eloquent SQL queries to extract data.
7+ years of related industry experience.
Excellent knowledge of SQL/NoSQL, comfortable with relational/nonrelational data models.
Experience in ML Operations and model deployment is a definite asset.
Excellent written and oral communication skills in English.
Highly self‑motivated and directed.
Ability to effectively prioritize and execute tasks in a high‑pressure environment.
Ability to travel upon request.
Preferred Skills
Experience with MLOps and deploying models in production environments.
Familiarity with cloud platforms (AWS, GCP, Azure).
Understanding of data governance, privacy and ethical AI.
Experience working in cross‑functional product teams.
Perks & Benefits
Annual Salary Increase Review
30 Days of Vacation Per Year
Comprehensive Insurance Coverage (Health, Oncological, Dental and Life Insurance)
Meal Allowance
English Course Subsidy/Language Assistance
Growth Opportunities
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
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