Sudeep Kadyan

Product Manager

Gurugram, Haryana, India4 yrs 9 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in transforming data into actionable insights.
Achieved less than 10% default rate in unsecured loans.
Strong background in credit risk management and data analytics.

Stackforce AI infers this person is a Fintech expert with strong capabilities in data analytics and risk management.

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Skills

Core Skills

Data AnalyticsDatabase ManagementRisk ManagementData VisualizationMachine LearningCredit Risk Management

Other Skills

PostgreSQLAmazon QuickSightREST APIETLPython (Programming Language)SQLTableauAmazon AthenaAdobe AnalyticsProblem SolvingCIBIL data analysisBusinessData MiningCredit Risk Model ImplementationCredit Analysis

About

As a Lead Consulting Engineer at Shifamed, I specialize in transforming complex data into actionable insights with AWS QuickSight and REST API integrations. I focus on optimizing inventory and database management, enabling seamless data access, and ensuring scalable analytics solutions. Collaborating closely with clients, our team develops and maintains ETL pipelines, ensuring reliable data flow and effective product implementation. My academic foundation includes a Post Graduate Program in Data Science & Engineering from Great Learning and a Bachelor of Technology in Mechanical Engineering from B.R.C.M. College of Engineering & Technology. With expertise in credit risk management and data analytics, I aim to deliver impactful solutions that empower smarter business decisions.

Experience

4 yrs 9 mos

Total Experience

1 yr 7 mos

Average Tenure

1 yr 8 mos

Current Experience

Shifamed

Lead Consulting Engineer

Oct 2024 – Present · 1 yr 8 mos · California, United States · Remote

Lead Consulting Engineer at Enlil.io, transforming complex data into actionable insights using AWS QuickSight.
Analyse and optimize inventory data, manage lots, and track parts with high precision and efficiency.
Build and integrate REST APIs to connect systems and enable seamless data access.
Handle database management (design, querying, performance tuning) to support scalable analytics.
Develop and maintain ETL pipelines to ensure clean, reliable, end-to-end data flow from source to dashboards.
Interact regularly with clients/customers to gather feedback, understand requirements, and demonstrate product implementations.

PostgreSQLAmazon QuickSightREST APIETLDatabase ManagementData Analytics

Mobikwik

Senior Data Analyst

Nov 2023 – Oct 2024 · 11 mos · Gurugram, Haryana, India · On-site

Risk Management: Oversee and manage risk metrics and cohorts for BNPL (Buy Now Pay Later) and Merchant Lending products,
ensuring robust risk assessment and mitigation strategies.
Portfolio Visualization: Lead the development and implementation of comprehensive portfolio visualization strategies to monitor
performance, identify trends, and drive data-informed decisions.
Collection and Fraud Strategy: Develop and execute strategies for effective collection and fraud prevention, enhancing the security
and efficiency of lending operations.
Data Analysis Tools: Using Tableau, QuickSight, and Athena for funnel monitoring and product enhancement, delivering
actionable insights, and driving strategic decisions.
Datamart Creation: Design and manage datamarts to optimize data organization and accessibility, supporting advanced analytics
and reporting.

Python (Programming Language)SQLTableauAmazon QuickSightAmazon AthenaRisk Management+1

Freecharge

Senior Business Analyst

Sep 2021 – Nov 2023 · 2 yrs 2 mos · Gurugram, Haryana, India · On-site

Strategy enhancement: Collaborated cross-functionally with teams such as marketing, finance, and engineering, ensuring seamless
integration of analytics insights into product development and marketing strategies.
Machine Learning Application: Utilized machine learning models to significantly reduce churn rates and develop a preapproved
base using CIBIL data, enhancing customer retention and creditworthiness assessments
Scorecard Development: Lead the development and refinement of scorecards to assess creditworthiness and manage risk effectively
in digital lending products.
Product Support: Using diverse data sources such as appographic(Device app) data, SMS data, and visit data to augment
traditional transactional data, enabling the creation of a comprehensive 360-degree view of the user base to generate new leads
and cross-selling capabilities