WeRize - Lead Data Scientist - AI/ML Solution

About the role : You will help solve problems at WeRize across credit/fraud risk, business, collections, customer service, etc through AI/ML techniques. As a key member of the team, you work closely with leadership and business/functional units to manage model lifecycle of build, validate, implement, monitor, and update. Responsibilities : - Solve business problems across all functions using AI/ML. - Ownership of model lifecycle management. - Guide and train junior team members. Key Responsibilities : - Build AI/ML solutions to solve business problems across credit risk, fraud, collections, customer service, and other business functions. - Own the complete machine learning model lifecyclefrom problem definition and model development to deployment, monitoring, and optimization. - Develop predictive and prescriptive models using structured and unstructured data. - Collaborate with business stakeholders to translate business challenges into data-driven solutions. - Mentor and guide junior data scientists and analysts. - Present analytical insights and recommendations to technical and non-technical stakeholders. Required Skills : - 4 to 8 years of hands-on experience in Data Science, Machine Learning, or Applied Analytics. - Strong proficiency in Python (mandatory) and SQL. - Experience building and managing ML models across supervised and unsupervised learning using structured and unstructured data. - Hands-on experience with one or more of the following: Credit Risk Scorecards, Fraud Detection, Propensity Models, Optimization, NLP, Classification, Regression, Clustering, and Model Lifecycle Management. - Strong analytical, quantitative, and problem-solving skills with the ability to translate business problems into scalable AI/ML solutions. - Excellent written and verbal communication skills with experience working directly with business stakeholders. - Self-driven, comfortable working in ambiguous environments, and capable of mentoring junior team members. - Demonstrable experience in financial services, fintech, banking, or lending with exposure to financial domain-specific model development.