Feedzai is seeking a Data Scientist to join our Customer Success team, working on the world's leading RiskOps platform for financial risk management powered by machine learning and artificial intelligence. In this role, you will engage directly with our clients, applying critical thinking and business acumen to understand their data, develop advanced models, and deliver best-in-class risk prevention solutions. You'll be at the forefront of fighting financial crime and protecting people from fraud while working with a collaborative, globally-distributed team. Your day-to-day responsibilities will include understanding and cleaning client data, preprocessing information using Python, Java, or Scala, iteratively developing and tuning machine learning models to improve quality, and communicating findings to project managers and stakeholders. You will work cross-functionally with data scientists, engineers, risk managers, and internal teams including Product and Research to continuously improve processes and tooling. This is an excellent opportunity for someone with a strong background in machine learning and big data technologies to make a direct impact on global commerce security, working with technology that protects 900 million people across 190 countries.
Responsibilities
- Understanding the data which clients provide
- Cleaning and validating data correctness
- Preprocessing data using shell scripts and programming languages such as Python, Java, Scala
- Iteratively computing features and tuning parameters to improve model quality
- Communicating findings to project managers and assisting in decision making
- Working with key stakeholders including data scientists, engineers, and risk managers from client organizations
- Collaborating with internal teams in Product, Research and other departments to improve processes, best practices and tooling
Skills
Benefits
- Immersive onboarding with training and one-on-one manager support
- Virtual and onsite shadowing opportunities with colleagues
- Access to comprehensive company history and knowledge resources
- Early project involvement and collaboration on ongoing work
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