Data Science Intern

InComm Payments

  • Brasil
  • Estágio
  • Período integral
  • Há 5 horas
Job Description:OverviewWhen you think of InComm Payments, think of Innovative Payments Technology. We were founded over 30 years ago and continue to be a pioneer in the payment (FinTech) industry. Since our inception, we have grown to be a team of over 3,000 employees in 35 countries around the world. We own over 400 global technical patents and a network that includes over 525,000 points of retail distribution that points to our industry expertise.InComm Payments is highly focused on our people and their growth, and we work hard to make a career at InComm Payments meaningful and rewarding. We value innovation, quality, passion, integrity and responsibility in all that we do, and we are looking for great people to join our team as we move forward towards a very bright future. We anticipate developing future leaders for our teams in Brazil!You can learn more about InComm Payments by visiting our or connecting with us on , , , , or .About This OpportunityAs a Data Science Intern within the Fraud Decision Sciences team, you will work on meaningful projects that help shape the company’s fraud mitigation strategies. In this role, you will leverage large-scale datasets to identify fraud patterns, contribute to predictive modeling efforts, and support the development of analytical tools that enable data-driven decision-making. This is a high-impact internship designed for students who want to apply advanced analytical techniques in real-world risk and fraud scenarios.You’ll work cross-functionally with product managers, fraud analysts, and technical teams to explore novel datasets, surface hidden insights, and improve fraud controls at scale.Why Join InComm?
  • Paid Internship
  • 30-hour work week, Monday – Friday
  • Real-world experience with a leading global company
  • Mentorship, professional development, and networking opportunities
  • Discover highlights from our internship program on Instagram — follow us @InCommInterns
Responsibilities
  • Analyze millions of transaction records to uncover fraud trends using Python, SQL, and/or PySpark
  • Assist in developing and validating machine learning models to support real-time fraud detection and risk scoring
  • Explore new signals from device, behavioral, or geographic data to improve fraud prevention
  • Help automate dashboards and reporting pipelines for fraud KPIs and alerting
  • Evaluate model performance and data quality, surfacing risks to data integrity and detection logic
  • Document your findings and present results to the broader team
  • Collaborate with cross-functional teams to gather requirements and understand the business context behind fraud patterns, ensuring the analytical solutions align with strategic goals.
  • Conduct exploratory data analysis to identify anomalies and significant features in datasets, providing actionable insights that can inform fraud risk management strategies.
Qualifications
  • Pursuing a degree in Data Science, Computer Science, Statistics, Engineering, or a related field within your penultimate or final year of study.
  • Above average academic track record
  • Strong foundation in Python for data analysis and/or machine learning with hands-on experience using pandas, scikit-learn, seaborn and other relevant libraries.
  • Familiarity with SQL for querying large datasets
  • Experience with tools like Jupyter, Power Automate, Power BI and Power Apps
  • Interest in fraud, cybercrime, or financial risk modeling
  • Clear communicator with a desire to learn in a fast-paced, collaborative environment
  • Ability to communicate clearly and professionally, both in writing and verbally
  • Proficiency with the English language
  • Must be self-motivated, ability to prioritize effectively and not shy away to seek guidance when you are blocked on a task
  • Ability to work with large teams; Willing and capable of learning new tools and technologies
InComm provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity or national origin, citizenship, veteran’s status, age, disability status, genetics or any other category protected by federal, state, or local law.

InComm Payments