Job Introduction

We are seeking a highly analytical and detail-oriented Senior Data Analyst to join our Lending Product team. In this pivotal role, you will be responsible for building the data infrastructure and analytical frameworks that drive our business, marketing and risk control strategies. You will work at the intersection of data engineering, business intelligence, and financial risk, transforming raw data into actionable insights that protect the organization's financial health and optimize our lending products.

Responsibilities:

Data Infrastructure & Architecture: Design and optimize risk-related database tables and variable libraries. Collaborate closely with the development team to ensure seamless implementation and high data integrity.
Strategic Business Monitoring: Proactively identify business issues through daily analysis. Partner with cross-functional teams to design, build, and maintain advanced BI dashboards that monitor key risk indicators (KRIs) and propose data-driven optimizations for risk control strategies.
Comprehensive Lifecycle Analysis: Independently lead data requirement analysis across end-to-end business processes. Contribute to the development of sophisticated user portraits (profiles) and standardized risk indicators to enhance behavioral forecasting.
Financial Modeling & Pricing: Participate in the estimation of expected losses (EL) and the strategic pricing of company products to ensure a balanced risk-reward profile.
Ad-hoc Analytical Support: Serve as a subject matter expert for the data department, handling complex, high-priority tasks that support broader organizational goals.

Requirements:

Education: Bachelor's degree or higher in a quantitative field such as Statistics, Applied Mathematics, Econometrics, or Computer Science.
Experience: Minimum of 5 years in a professional data analysis role. Prior experience in Inclusive Finance, Digital Personal Loan, or Non-Performing Asset (NPA) management is highly preferred.
Domain Expertise: Proven track record in implementing data monitoring projects and a deep familiarity with credit risk indicators (e.g., delinquency rates, vintage loss, exposure at default).
Technical Proficiency:

-Expertise in SQL for complex data extraction and manipulation.

-Proficiency in at least one statistical programming language: Python, SAS, or SPSS.

-Experience with BI tools (e.g., Tableau, Power BI) for data storytelling.

Soft Skills:

-Exceptional problem-solving abilities and report-writing skills.

-Must possess strong communication skills to effectively translate technical findings for

non-technical stakeholders and collaborate with engineering teams.

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