Decision Science Analyst

Job Title: Credit Decision Science Manager

Location: India/Australia

Position Summary: We are seeking a highly skilled Credit Decision Science Manager to spearhead our credit decisioning strategies, particularly in the cash advance and lending products domain. This role calls for a blend of analytical expertise, strong leadership abilities, and excellent communication skills to drive innovation in credit decision processes.

Key Responsibilities:

• Develop, implement, and optimize advanced credit decisioning models and frameworks for merchant cash advance, lending, and merchant acquiring products.
• Analyze extensive data sets to identify trends in credit behavior and transaction processing patterns to make informed decision-making and risk assessment.
• Continuously monitor and refine credit risk models in response to changes in the local economic environment, regulatory landscape, and credit behavior trends.
• Conduct thorough risk assessments and scenario analyses to evaluate portfolio performance and recommend proactive mitigation strategies.
• Ensure that credit decisioning and transaction monitoring processes and systems are compliant with both internal policies and external regulatory requirements.
• Collaborate with cross-functional teams, including product management, IT, compliance, and lending operations, to align credit risk strategies with business objectives.
• Monitor credit risk exposure on periodic basis, ensuring compliance with internal policies and external regulatory requirements, and adjusting strategies based on market trends and business needs.
• Stakeholder Engagement: Effectively communicate complex analytical concepts and credit risk insights to senior management and stakeholders, ensuring alignment with the overall business strategy in Australia
• Present complex quantitative analyses and insights clearly and concisely to stakeholders at various levels, including senior leadership.
• Mentor and guide a team of analysts, promoting best practices in credit risk modeling and data analysis.
• Create training materials and presentations to educate internal teams about credit risk methodologies, tools, and policies.
• Stay informed on industry trends, emerging technologies, and regulatory changes, proactively adapting strategies to ensure competitive advantage.
• Collaboration: Develop constructive relationships with credit bureaus, vendors and industry peers to stay informed about local credit trends, changes in credit reporting, and emerging risks in the market.
• Keep abreast of industry best practices and advancements in credit analytics, exploring innovative approaches to enhance credit decision frameworks through machine learning and other advanced technologies.

Qualifications:

• Bachelor's degree in Statistics, Data Science, or a related field; a Masters degree is preferred.
• Minimum of 5 years of experience in credit risk management or decision science, specifically within the lending or cash advance arena.
• Demonstrated expertise in quantitative analysis, credit risk modeling, and the ability to interpret complex datasets to extract actionable insights relevant to the Australian market.
• Expertise in statistical methods and data analysis tools (e.g., SQL, Python, R, SAS).
• Exceptional communication skills, with the ability to articulate complex analyses to non-technical stakeholders effectively.
• Proven experience in managing stakeholder relationships with a focus on cross-department collaboration.
• Strong leadership qualities, demonstrating the ability to inspire and motivate team members to achieve performance goals.
• Critical thinking and problem-solving aptitude, with a proactive approach to identify opportunities for improvement.

Preferred Skills:

• In-depth knowledge of credit risk assessment methodologies and practices.
• Experience with advanced analytics techniques such as machine learning and AI in the context of credit risk modeling.
• Understanding of the financial services industry's dynamics, including competitive trends and consumer behavior patterns.