Data Scientist - (Risk Analyst)

This role is for one of the Weekday's clients

Min Experience: 6 years

JobType: full-time

This role is responsible for leading a team of 6-8 data analysts to deliver high-quality descriptive and diagnostic analytics across multiple product lines and business functions. The position involves generating timely insights, supporting analytical decision-making, and driving automation for recurring reporting and stakeholder requirements. It also plays a key part in strengthening risk models and enhancing analytical capabilities across the organization.

Requirements

Key Responsibilities

• Lead a team of data analysts to produce accurate MIS reports, variance analyses, and actionable insights within defined timelines.
• Conduct descriptive and diagnostic analytics across product portfolios and business verticals including acquisitions, cross-sell, customer service, and collections.
• Support stakeholders with data extraction, data manipulation, and operational analytics needs.
• Identify reporting gaps and recurring analytical requirements to automate dashboards in Tableau.
• Replicate and scale insights and reporting processes across different products and functions.
• Collaborate with business teams and modelling teams to provide analytical inputs that sharpen and improve ML model performance and usage.
• Drive the design, development, and deployment of ML/DL models supporting underwriting, portfolio management, and risk assessment.
• Monitor and enhance credit risk frameworks including Expected Credit Loss (ECL), vintage analysis, delinquency analysis, and other risk measurement methodologies.
  
  

Required Skills & Qualifications

• Experience: Minimum 8 years of experience in descriptive and diagnostic analytics within NBFC / BFSI or FinTech.
• Education: M.Tech / B.E / B.Tech / M.Sc in Computer Science, Statistics, Mathematics, or related field.
• Technical Expertise:
• Strong hands-on experience in SQL and Python.
• Proficiency in Tableau and Excel for dashboards, automation, and business insights.
• Experience with ML/DL model development and deployment.
• Risk Analytics Expertise:
• Credit risk modelling, portfolio monitoring, operational risk, and Expected Credit Loss (ECL).
• Time series forecasting, vintage and stress testing, simulations, and design of experiments.
• Delinquency analysis and On-Us / Off-Us analysis using credit bureau data.
  

Industry Exposure

• BFSI (Banking, Financial Services & Insurance)
• FinTech