Risk Analytics Role (6-10 yrs)

About Drip Capital:

Drip Capital is a high-growth FinTech focused on the $5T global SME cross-border trade industry. We offer innovative trade financing targeted at small businesses in developing markets, providing rapidly growing SMEs with quick and easy access to finance. With a focus on technology, our vision is to eliminate the hassle of paperwork and bureaucracy and create seamless borrowing experience for its customers.

Our team comprises talent from top-tier institutions including Wharton, Stanford, and IITs with years of experience at companies like Blackrock, Goldman Sachs, Google, McKinsey. We are backed by leading Silicon Valley investors - Sequoia, Wing, Accel, and Y Combinator. We are a global company headquartered in Silicon Valley along with offices in India and Mexico.

Risk - Strategy & Analytics:

Risk Analytics team at Drip Capital is at the cutting edge of innovation, sitting at the core of our business operations to shape and execute the company's risk strategy. Leveraging advanced artificial intelligence (AI), machine learning (ML), and predictive analytics, the team develops forward-looking, scalable models to drive real-time decision-making and optimize risk management processes.

We integrate AI-driven insights into our operations, utilizing techniques such as regression modelling, time series analysis and generative AI to enhance decision accuracy. Collaborating closely with various stakeholders, including business growth, the CEO's office, risk operations, product development, and technology teams, we ensure seamless alignment of risk strategy with company objectives.

Our mission is to foster sustainable, data-driven business growth by creating robust risk policies, applying portfolio optimization, and harnessing next-gen analytics for risk mitigation and opportunity identification.

Your Role:

You will lead high-impact projects aimed at mitigating risk and optimizing Drip's portfolio across diverse products and markets. You'll harness advanced analytics, predictive modeling, and data-driven insights to enhance risk strategy, improve underwriting models, and conduct in-depth portfolio performance analysis, ensuring alignment with the company's risk appetite framework.

Key Responsibilities:

- Develop risk policies using data analytics to drive business growth while maintaining robust portfolio risk controls.

- Utilize portfolio analytics to monitor risk metrics, identify trends, and ensure losses remain within defined risk tolerance levels.

- Lead and mentor a team of 3 to 4 analysts, driving innovation and analytical rigor.

- Collaborate with product, technology, operations, and risk servicing teams to design and implement scalable global risk strategies leveraging AI ML-based risk models.

- Conduct root cause analysis using statistical tools to identify policy gaps, optimize processes, and ensure regulatory compliance.

- Champion data-first decision-making by leveraging tools like SQL, Python, and visualization platforms (e.g., Tableau, Power BI).

- Deliver comprehensive risk dashboards and data visualizations to senior management and stakeholders, enabling actionable insights.

- Redesign and enhance risk policies, incorporating predictive risk scoring models, financial ratio analysis, and dynamic monitoring mechanisms.-

- Define and implement credit approval policies leveraging advanced credit risk modeling techniques, ensuring strategic alignment.

Our Checklist:

- 5 to 10 years of experience in analytics-driven roles within Tier 1 or 2 financial services, consulting, or FinTech (experience with early or growth-stage FinTech is highly preferred).

- Graduate from a Tier 1 or 2 institution with a degree in engineering, statistics, finance, or MBA.

- Advanced certifications like CA, CFA, FRM, or equivalent are a strong plus.

- Expertise in SQL, Python, and familiarity with machine learning frameworks (e.g., regressions, time series modelling).

- Demonstrated ability to build statistical models, perform data mining, and create predictive analytics for risk management.

- Proficiency in data visualization tools like Tableau, Power BI to communicate findings effectively.

- Strong analytical acumen, with a proven track record of translating complex datasets into actionable business insights.8. Exceptional communication and collaboration skills, with experience working in cross-functional environments.