Data Scientist I
About the role
About Mozn
MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.
We're a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.
If you're passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.
About the role
The Mozn brand is alive within a plethora of stakeholder touchpoints and therefore the most suitable candidate for the Data Scientist I position would have an interest in Financial Fraud Detection, Sanction Screening, Know Your Customer (KYC) procedures, Anti-Money Laundering (AML) initiatives, and emerging Generative AI technologies. As a Data Scientist I, you will support the development of analytical and AI-driven solutions to help detect and prevent fraudulent activities and mitigate AML risks under close guidance.
What you'll do
- Support the development of fraud detection, AML, and Generative AI use cases.
- Assist in building and testing ML and GenAI models (e.g., prompt engineering, RAG pipelines).
- Prepare, clean, and analyze structured and unstructured data.
- Support the training, evaluation, and deployment of ML models.
- Assist with experimentation using LLMs for tasks such as document analysis, alert summarization, or data enrichment.
- Execute assigned tasks within project plans under supervision.
- Stay informed about industry trends related to fraud, AML, and Generative AI.
Requirements
- Bachelor's degree in Data Science, AI, Machine Learning, Mathematics, Statistics, or a related field.
- 0-2 years of experience in data science or analytics.
- Basic understanding of ML concepts and…