Quant, Python developer, trading

SUMMARY Seeking a position as Junior Quantitative Developer / Researcher / Data analyst. Experience in

working at a big international bank in risk department. Experience in working as a quantitative

researcher at a hedge fund. Directly involved with senior traders and managers to build and test

strategies for various asset groups. Self-starter with excellent problem solving and real-time production

level expertise. Currently working with RB (multinational CPG) as a Business analyst

SKILLS Quants: Options trader using Greeks (Alpha, Gamma, Theta, Beta) analyzing market volatility, bid-ask

spread, type of order to execute, Equities Trading Strategies, Quants, Econometrics, Risk,

Arbitrage and Special Market events trading (Like M/A, Earnings, Political moves, Brexit, Elections)

IT: Machine Learning, Data Science, SQL, Python, Pandas, NumPy, R, Django, Programming, Excel,

OOPS and concepts, HTML5, Bootstrap, CSS, Bloomberg Terminal, Power Bi, Web developer,

Shell, OOPS & concepts

Personal Skills: Poker player, Hardworking, Excellent coder, Analytical approach towards problems,

Ability to work under pressure, Expeditious, Pattern recognition, Entrepreneurial skill set

EXPERIENCE Reckitt Benckiser, Parsippany, NJ Jan 2019 – Business Analyst / Python Developer

(Role: Financial analytics, accrual accounting, client trade performance/optimization, ROI forecast)

• Building automation tools in Python/Django for data analysis, reusable code for analysis of financial statements and earnings estimates. Building Power BI reports for performance reviews • Analysing trade desk transactions and reports for trade cost, market bid-ask spread and market volume(liquidity) specially for Options and equity markets • Assisting IT department in adopting and migrating the current trade platform from C++ to Python. Giving access to the qualified users to the Siebel platform and trade approval limits by managing requests and tickets. • Budgeting and forecasting of volumes, pricing and trade investment, providing financial support in contract negotiations, measuring and evaluating trade spend effectiveness • Enterprise Edition (OBIEE) imbedded analytics, develop and report sales forecasts and provide analysis to the business. Responsible for data management and integrity to ensure strategic P&L financial accrual expectations are met. • Analysing discrepancies in balance sheet, trades and cashflows, analysing trade spent and ROI

Jefferies (Investment Bank), New York, NY Aug 2018 – Dec 2018

Quantitative Risk Analyst Intern

(Role: Alpha search, Factor modelling, Programming financial risk tool in Python)

During my internship, I did a POC (In Django/SQL) on a sentimental data, where I built a python

platform used by risk managers to be aware of sentiment risk attached with stocks in accounts. The

platform provided -

• Doing risk modelling for interest rate risks – Asset Liability Modelling. Calculating effects of

duration and interest sensitivity, NII (Net Interest Income), MVE (Market Value of Equity)

• Historical sentiment screener, the sentimental risk associated with accounts

• Predicting stock direction using today’s and previous days sentiment data

• Return based on Quantiles of Sentiments, prob. of making a catching right trade direction

• A sentiment ticker screen where stocks tick with news coming in Design algorithms for confirming the reliability of the sentimental stock which varied with stocks

• Help in data migration, cleaning data both structured and unstructured and ensuring a proper pipeline is maintained for Quantitative research team

• Building an ALM modelling to reflect how change in interest rates are affecting the bank balance sheet. Made use of duration, market risk, NII to model out interest rate risk.

PlusPlus Capital Management (Hedge Fund), Jersey City, NJ June 2018 - Aug 2018

Quantitative Research Intern

• Back-testing new options trading ideas, analyzing existing futures & options strategies. Creating R

program to facilitate analysis of trading strategies & presentations based on statistical findings

• Studying market inefficiencies in futures markets using historical data and forming statistical

conclusions. Doing in-depth research on implied volatilities of various futures markets and exploring

the statistical properties of implied volatilities

• Designed python web crawlers to scrape daily financial data from websites and updated the

database. E.g. WSJ NHMNL data

• Some trading strategies I have tested and designed

- Backwardation/Contango in commodity market - Analyzing sector performance in bull/bear market

- Quadruple Witching-200-day MA strategies on S&P500 - Turn of the month effect

- Predicting direction of IV on various threshold levels

KTZ Capital Jan 2016 - Dec 2017

Founder, Options & Equity Trader

• A team of 3 people including me designed strategies to invest in options market by analyzing market

liquidity & global news. Some basic options strategies I used - Spreads, Covered Call, Iron Butterfly

• Developed financial market sentiment analysis and stock screening applications on Python Django

• Managed 100,000 for the firm and investments in Indian markets. Traded options, equity and futures

EDUCATION Stevens Institute of Technology, Hoboken, NJ Aug 2017 - Dec - 2018

Master’s in Financial Engineering, GPA: 3.78

Course Work: Computational methods in finance, Market Microstructure & Trading, Stochastic

Calculus, Quantitative Finance

SRM University, Bachelor’s in Computer Science, in GPA: 8.2 Jun 2013 - May 2017

ACADEMICS Computational Finance & Stochastic Calculus Spring 2018

• Programmed Black Scholes model in R for estimating implied volatility & option prices with

bisection method, it helped me to explained volatility smiles existence & Put-Call parity

• Solving Stochastic models for investing and implementing trading strategies. E.g. Pricing options,

interest rate variation with Vasicek and CIR models, understanding volatility behavior from

stochastic processes. Working with Binomial & Trinomial trees to price options

• Implementing Monte Carlo Stimulations based on Euler Milstein discretization, antithetic variates

method, delta-based control variate to price various option types

LinkedIn: https://www.linkedin.com/in/kshitiz-sharma/

Sample Work (All code is in Python)

1)Stock Investment – Technical Analysis

a.https://github.com/KshitizSharmaV/DataScience_In_Investment_Banking/blob/master/TSLA%20technical%20analysis.ipynb

2)Supervised Learning

a.https://github.com/KshitizSharmaV/DataScience_In_Investment_Banking/blob/master/Supervised%20Machine%20Learning.ipynb

3)Unsupervised Learning

a.https://github.com/KshitizSharmaV/DataScience_In_Investment_Banking/blob/master/Unsupervised%20Machine%20Learning.ipynb

4)Statistical Analysis:

a.https://github.com/KshitizSharmaV/DataScience_In_Investment_Banking/blob/master/Statistical%20Analysis.ipynb

5)Time Series Analysis:

a.https://github.com/KshitizSharmaV/DataScience_In_Investment_Banking/blob/master/Time%20Series%20Analysis.ipynb

6)My upcoming Web based Quant Analytics platform based on Python, HTML5 :

https://github.com/KshitizSharmaV/Quant_Platform_Python

Kshitiz Sharma

M.S Financial Engineer & B.Tech Computer Science

911 Washington Street, Apt 3, Hoboken, NJ 07030, 551-***-****, ****************@*****.***

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