Shweta Agrawal

AI Researcher

Ghaziabad, Uttar Pradesh, India6 yrs 4 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

6+ years of experience in Data Science and Quantitative Research.
Expert in developing ML models for financial products.
Proficient in cloud application deployment and stakeholder management.

Stackforce AI infers this person is a Fintech Data Scientist with expertise in quantitative modeling and machine learning.

Contact

Skills

Core Skills

Machine LearningStakeholder ManagementPricing ModelRisk Neutral FrameworkMonte Carlo SimulationRisk MeasurementK-mean Clustering

Other Skills

AWSAdvanced MathematicsAmazon Web Services (AWS)Asset Pricing theoryBERT (Language Model)Big Data AnalyticsBootstrappingClimate RiskConstrained OptimizationCorporate FinanceDecision TreesDerivatives AnalysisESG RiskEconometric ModelingEnsemble Models

About

• Self-motivated performance driven Data Scientist with 6+ years of experience in Quantitative Research and Quantitative Model • Development for Financial Products (Lending (Credit), & Equity) using Machine Learning and Advanced Mathematical Techniques such as Probability Theory, Statistics, Derivatives and Linear Algebra. • Working experience of ML models such as Linear and Non-Linear Regression, Decision Trees, Random Forest and XGBoost, Clustering, Regularization, Bootstrapping, Ensemble Learning and Neural Network. • Developed and deployed applications on cloud platforms such as AWS, with proficiency in writing production level dynamic and efficient code in Python, R/ R-Shiny, Excel, PySpark, VBA, SQL, and Hadoop and leveraged GIT for version control. • Financial working knowledge of Risk Management, Expected Credit Loss, Climate Adjusted PDs, NGFS Scenarios, ESG & Climate Risk, RAROC, Scorecard development, Capital Asset Pricing Model (CAPM), Vasicek & Merton Model and Derivatives Pricing. • Extensive experience in stakeholder management, leading and training team of junior tech-consultants, and mentoring them. • Developed and implemented models for major Global Commercial & Development Banks across Middle east, APAC, and Europe.

Experience

Moody's analytics

2 roles

Senior Risk Consultant

Promoted

Nov 2023 – Present · 2 yrs 4 mos · Gurugram, Haryana, India · Hybrid

Pioneered development of ML algorithm utilizing Regression, and Random Forest to estimate ESG metrics, including ESG scores and
Carbon Emissions Footprint, for any firm across 96 countries worldwide.
Build XGBoost and Forward & Backward Logistic Regression models for various segments of retail consumers to determine TTC PD for
~1million customers as a part of scorecard building exercise.
Designed Logistic Regression model on a Bootstrapped dataset for a low default and small sized portfolio which the aim of estimating PD.
Designed Commodity Trading Scorecard using Generative Algorithm Optimization technique for weight estimation, facilitating the bank
with PD and rating for the commodity trading borrowers.
Minimum Required Rate of Return estimation using CAPM for relationship between Expected Return and Risk of investing in a security

Climate RiskStakeholder ManagementESG RiskPricing ModelMachine LearningConstrained Optimization+1

Risk Consulting Associate

Dec 2021 – Nov 2023 · 1 yr 11 mos · Gurugram, Haryana, India · Hybrid

Build quantitative framework to estimate Portfolio Return & Risk measures like Economic Capital, Unexpected Loss, Sharpe Ratio etc. which
is helping >100 small and medium sized banks across world in estimating and reporting their Capital corresponding to Unexpected Loss.
Developed and implemented pricing models, including the Risk Adjusted Return on Capital (RAROC) framework, via a cloud-based
application, offering banks a competitive advantage over traditional methods.
Developed a quantitative framework for calculating Expected Credit Loss for Credit Derivative Products such as Credit Default Swaps,
aiding banks in estimating Expected Losses for borrowers with very less PD.

Risk Neutral FrameworkVasicek and Merton ModelMonte Carlo SimulationBootstrappingAmazon Web Services (AWS)R Shiny+1

Paytm

Senior Associate (Risk - Analytics)

Jun 2021 – Nov 2021 · 5 mos · Noida · Remote

Developed interactive risk control dashboard for continuous monitoring of risk parameters bifurcated at various level like segment, portfolio, asset class etc.
Leveraged clustering analysis (K-Means Clustering) to segment ~0.1 million customers for devising tailored strategies to optimize loan repayment from each group.
Implemented Linear and Logistic Regression to determine credit eligibility and limit for ~7 million customers

Ensemble ModelsPySparkK-Mean ClusteringBig Data AnalyticsRisk Measurement

Nielsen

Analyst

Jul 2020 – May 2021 · 10 mos · Baroda

Carried out Feature Selection Techniques such as using Forward Selection, Backward Elimination and Regularization Techniques (Ridge, Lasso)
Built Market Mix Models to quantify the impact of media execution on sales - to analyze the relationship between paid media and sales and then calculate media impact
Leveraged advanced data analysis techniques to identify patterns and trends in market data, enhancing decision making process