Lead - Data Science

• Build and improve Machine Learning models to power recommender systems, personalization, and user engagement use cases.
• Work closely with Product and Business teams to define Machine Learning problems and translate them into scalable data products.
• Collect, clean, and prepare large-scale datasets for modeling and analysis.
• Design and engineer features, experiment with new approaches, and continuously improve model performance.
• Deploy and productionize Machine Learning models in live systems with reliability and scalability in mind.
• Design, run, and analyze A/B tests to evaluate the impact of the model and generate actionable insights.
• Build and maintain pipelines for continuous model validation, monitoring, and retraining.

• At least 5 years of working experience with 3 years of hands-on Machine Learning experience, or 2+ years with a PhD in a relevant field.
• Strong understanding of the mathematical foundations behind Machine Learning algorithms.
• Proven experience applying Machine Learning to personalization, recommender systems, user behavior analysis, or credit scoring.
• A strong builder mindset with the ability to take models from prototype to production.
• High product ownership with a strong sense of responsibility for quality, impact, and long-term maintainability.
• Strong collaboration skills and willingness to actively support and mentor team members.
• Experience with credit scoring or financial services models is a plus.