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VP - Quantitative Analytics
Quantitative analytics leader with deep expertise in risk AI/ML model development, Generative AI (GenAI), and agentic AI deployment, alongside regulatory frameworks (ICAAP, CCAR, Stress Testing) and portfolio risk management. Proven track record of building high-performing analytics teams from the ground up and establishing scalable modeling frameworks, governance standards, and best practices. Experienced in delivering Monte Carlo VaR, credit risk, and fraud detection models, while leading teams, driving innovation, and aligning analytics initiatives with business strategy. Strong mentor and cross-functional collaborator.
Indian School of Business
Advanced Management Programme in Business Analytics
April 1, 2016 – January 1, 2018
WorldQuant University
Masters, Financial Engineering
N/A – Present
St. Francis' College, Lucknow
High School,Maths with Computer Science
N/A – Present
Barclays
Vice President - Enterprise Risk Analytics
November 1, 2022 – Present
Barclays
Assistant Vice President - Quantitative Analytics
April 1, 2020 – October 1, 2022
Barclays
Assistant Manager - Quantitative Analytics
September 1, 2018 – March 1, 2020
FIITJEE
Manager - AI Strategy
February 1, 2018 – September 1, 2018
Ericsson
Data Scientist - Workforce Strategy & Analytics
April 1, 2017 – February 1, 2018
Gurgaon, India
WNS Global Services
Senior Associate - Research & Analytics
September 1, 2015 – April 1, 2017
Gurgaon, India
Cultural Fit Analysis
The candidate has a strong background in financial services (Barclays) and analytics, which aligns well with roles requiring robust data analysis and risk management. However, the target role is 'Data Analyst', which might be a step down from their 'Vice President' and 'Manager - AI Strategy' roles, potentially indicating a mismatch in career progression or a desire for a more focused technical role. The breadth of experience across different companies (Barclays, FIITJEE, Ericsson, WNS) shows adaptability, but the long tenure at Barclays suggests a preference for stability within large organizations. The lack of diverse project descriptions outside of financial risk makes it difficult to fully assess cultural fit for broader data analyst roles.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership, stakeholder management, team mentorship, and driving innovation, suggesting strong soft skills relevant for senior roles. The focus on enterprise-wide solutions and regulatory compliance indicates an operational fit for structured, high-governance environments.