Niharika Prasad

VP of Engineering

New York, New York, United States7 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Python, Analytics, SQL, and Machine Learning.
Runner-up in Morgan Stanley Data Challenge.
Experience in liquidity risk management and stress analysis.

Stackforce AI infers this person is a Fintech expert with strong capabilities in data science and quantitative analysis.

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Skills

Core Skills

Liquidity Risk ManagementStress AnalysisData ScienceRisk PricingAnalyticsSoftware Development

Other Skills

AlgorithmsPython (Programming Language)Advanced SQLCData StructuresDerivativesStructured NotesTransfer PricingPricing StrategyStatistical AnalysisProblem SolvingAnalytical SkillsSwapsFxPrime Brokerage

About

VP, Quant Strats, Citi NY Expertise in Python, Analytics, SQL, and ML. Morgan Stanley Data Challenge Runner-up. Worked as Sofware Developer in Adobe Inc. Software development Intern in Samsung Research Institute, Bangalore (SRI-B) -5 months

Experience

7 yrs 11 mos

Total Experience

2 yrs 7 mos

Average Tenure

4 yrs 2 mos

Current Experience

Citi

2 roles

Vice President, Quant Strats, Markets Funding and Liquidity

Promoted

Oct 2024 – Present · 1 yr 8 mos

Markets Funding and Liquidity Management,
Unified Market Shock Framework : market shocks across all assets, reflecting a realistic macro trigger, for all stress scenarios including 2025 inflationary and deflationary impacts (Impact: Reducing reserves firm-wide and increase in savings, aid to FTP, XVA)
Secured and Unsecured Liquidity Impact
Stress Scenario Analysis
Stress VM analysis for businesses
Liquidity Framework (Helping to meet timelines communicated to the Fed)
Resolution and Recovery Planning (Enabling deep dives in complex cashflow derivations)
Enhanced VM Stress Model
CTI CRMR Rebate Process
Implementation of Markets Funding Strategy

Stress AnalysisLiquidity Risk Management

Assistant Vice President, Markets Innovations

Apr 2022 – Oct 2024 · 2 yrs 6 mos

Data Scientist at Citi's ICG Global Markets
Price Detection
Risk Pricing
Trade hit miss
Sales Intensity
Conversational Analytics
NLP models
Trade Analytics
Products - Swaps, FX, PB, Equity derivatives

AlgorithmsPython (Programming Language)Data ScienceRisk Pricing

Braze

Data Services Intern, Growth Engineering

Jul 2021 – Aug 2021 · 1 mo · New York, New York, United States

Braze: It is a customer engagement platform used by businesses for multichannel marketing.
Role: Data Services and Analytics in Growth Engineering
Worked on an Analytics Service project for the Esteé Lauder Companies, to support their strategic teams in their decision-making and advise them on data/analytics best practices in the Customer Engagement sphere for different channels.
Performed market research on KPIs, built them by handling a very large amount of data, using data engineering in Snowflake (language - Advanced SQL), and created visualizations dashboards in Looker with recommendations.
Metrics and analysis explored - Marketing Pressure (Frequency and Cadence), Best and worst performing campaigns and channels, Funnel Analytics, Propensity Score and Modeling, Conversion behavior, Segmentation using RFM (Recency, Frequency, and Monetary) Analysis

Python (Programming Language)

Adobe

2 roles

Senior Software Developer Engineer

Promoted

Feb 2019 – Feb 2021 · 2 yrs

Core Developer for CoreTech libraries and frameworks mainly PDF, and Release Engineering
Participated in migration of CoreTech libraries(PDF, CoolType, AGM, etc) from Desktop applications to WebApps.
Languages: C++, Python

CData StructuresSoftware Development

Software Developer Engineer

Sep 2017 – Jan 2019 · 1 yr 4 mos

Core member of Release Engineering and Installer generation for Adobe Creative Cloud/ Creative Cloud Desktop, ACPL (Cloud Tech), CoreSync, etc.
Languages and Technologies: Python, Perl, Jenkins

CData StructuresSoftware Development

Samsung electronics

Student Trainee

Jan 2017 – Jun 2017 · 5 mos · Bengaluru, Karnataka, India

Developed deep tagger criteria and slot handler to classify various user utterances into their right domain using NLTK, Gensim, and Stanford NER, which significantly improved Samsung’s virtual assistant, Bixby.

Python (Programming Language)