Data Science Lead (Remote)

SUMMARY:

Data Science Lead will enhance our Credit risk Data Science function, playing a pivotal role in shaping the future of data science and risk management in a dynamic, cross-collaborative environment at Jenius Bank. The ideal candidate will have a strong background in the consumer financial services industry with a focus in developing Credit risk models and data driven strategies, using bureau and alternative data. You will analyze the data and propose business use cases for risk in collaboration with Credit, Product, Fraud and compliance teams and develop models or data driven insights and strategies using ML or/and traditional statistical methodologies. Data Science lead will drive full lifecycle of compliant model development and approval process at the bank.

PRINCIPAL DUTIES AND RESPONSIBILTIES:

• Build and deliver advanced models for credit underwriting, account management and collections, utilizing both traditional credit bureau data and alternative sources such as bank transactional data, and employment data
• Develop model documentation and lead the approval process with Model Validation, second line and regulators.
• Work closely with Risk, Engineering, Product, Compliance and Analytics leadership to chart the roadmap for core risk decision-making and strategy, collaborating with cross-functional teams to shape the strategic direction of data science initiatives.
• Lead, mentor, and develop a high-performing team of data scientists and analysts, fostering a culture of transparency, innovation, and continuous improvement
• Ensure best practices in model development, deployment, and monitoring, while maintaining comprehensive documentation of processes, methodologies, and outcomes
• Communicate insights and model performance to senior management and stakeholders, ensuring alignment with business objectives and regulatory requirements
• Foster a culture of innovation through adoption of emerging technologies in Machine Learning and AI
   

POSITION SPECIFICATIONS:

• 7+ years of experience, with at least 4 years in the Consumer financial services industry or a PhD with at least 5 years of professional experience.
• A bachelor’s degree in mathematics, finance, industrial engineering, statistics, data science, or a related discipline; a master’s degree in these fields is preferred
• Expertise in design and build of risk underwriting and account management models that leverage alternative data, such as bank transactional data and specialty bureaus
• Strong expertise in statistical modeling methodologies, including ML and logistic regression, advanced data analysis techniques and reject inferencing.
• Proficiency in Python and SQL, familiarity in working with GCP and Vertex AI is a plus
• Experience with reporting tools like Power BI or Looker.
• A data-driven approach to solving complex business challenges, with the ability to break down difficult problems into actionable solutions
• Knowledge of credit products like Personal loans and Credit cards, with a strong understanding of credit underwriting, loan economics, and portfolio management
• Exceptional communication skills, enabling you to convey complex ideas clearly and effectively to diverse audiences, including non-technical stakeholders
• Creative problem solving, critical thinking skills, and get things done attitude