Associate Software Yoga Instructor

TEJUS SETLUR

*******@***.*** 929-***-**** https://www.linkedin.com/in/tejus-setlur/ https://github.com/tejusCodingBeast EDUCATION

NEW YORK UNIVERSITY, TANDON SCHOOL OF ENGINEERING Brooklyn, NY Master of Science in Financial Engineering Expected 05/24 GPA: 3.67/4.0

JSS SCIENCE AND TECHNOLOGY UNIVERSITY Mysore, Karnataka, India Bachelor of Engineering in Computer Science

GPA: 8.4/10.0

07/20

PROGRAMMING / TECHNICAL SKILLS / CERTIFICATIONS

● Languages: Scala, Python, SQL, C++, C, R

● Analytical Engine and Tools: Spark, Hadoop Apache Airflow, Jupyter Notebook, Spyder, Excel, Alteryx

● Certifications: Bloomberg Market Concepts, Quantexa Certified, Corporate Finance, Principles of Economics. Machine learning A-Z, Red Hat Openshift I

● Skills: Trading Strategies, Quantitative Methods in Finance, Financial Simulation, Time Series Analysis, Machine Learning, Neural Networks and Deep Learning, Portfolio Construction & Optimization, Big Data Analytics, Data Mining EXPERIENCE

NEW YORK UNIVERSITY, TANDON SCHOOL OF ENGINEERING, Brooklyn, NY 01/23 - Present Course Assistant, Machine Learning in Finance

● Provide supportive content, improve quality of presentations, and answer questions of students each week.

● Act as a liaison between the professor and the students, provide assignments and grade all work of students. DANSKE BANK, Bangalore, India 07/20 - 07/22

Associate Software Engineer, Financial Crime Prevention Department

● Designed, developed and tested software using Spark, Hadoop, and Scala as part of Trade Flow Monitoring squad to flag money laundering behavior on large transactional data from Foreign Exchange, Equities, Repo, Fixed Income and Structured Products.

● Automated and scheduled the workflow of transforming and analyzing transactional data by designing, developing and maintaining Direct Acyclic Graphs on Apache Airflow and deploying onto Openshift pods.

● Utilized Jupyter Notebook with Scala/Python for sampling and modeling to obtain statistical inference for reducing false positives and improving quality of Suspicious Activity Reports

● As a Subject Matter Expert, helped other squads on setting up Airflow and recruited for my squad by taking interviews. RESEARCH & ACADEMIC PROJECTS

NEW YORK UNIVERSITY, TANDON SCHOOL OF ENGINEERING

Pairs Trading With Statistical and Machine Learning Method (IAQF competition) 12/22 – 3/22

Identified pairs using statistical methods such as mean reversion, stationarity, ADF test, Cointegration-Engle and Granger test, Hurst Exponent,etc; and ML methods such as K-Means, Hierarchical Clustering, Affinity Propogation Clustering.

Implemented 3 trading strategies – Baseline strategy: leverages deviation from calculated fair value (Returns: 0.24%), Copula strategy: computes conditional probabilities based on different information criterion score (Returns: 1.52%), Reinforcement Learning Trading Agent: learns trading from experience using Deep Q Networks (Returns: 15.65%). Portfolio Optimization with Deep Learning and Black-Litterman (Professor Daniel Totouom Tangho) 09/22 - 12/22

Implemented and compared different portfolio optimization techniques such as Black-Litterman, Deep Learning, Mean Variance, and an all-weather model. Used ETFs of market indices to select a portfolio so multiple assets are optimally included.

The Deep Learning model used an input layer, an LSTM neural layer, and a softmax activation function for the output layer. This model optimized the Sharpe ratio and the result was 1.833, the highest compared to all other models.

The Black-Litterman model calculated implied excess equilibrium returns and incorporated the views vector and confidence in our views. We estimated the excess returns with a weighted average and used B-L formulae to obtain a Sharpe of 1.501 Pricing and Hedging of Up-and-Out Call Option (Professor David Shimko) 11/22 - 12/22

Priced OTC up and out call option for SNP500 using 5,000 Monte Carlo simulation of Geometric Brownian Motion.

Used Option chain data and secondary option prices to implement real time pricing of option

Devised and priced multiple low-cost bull spread hedging strategy using secondary options prices to offset the exposure JSS SCIENCE AND TECHNOLOGY UNIVERSITY

Paradigm for Business Intelligence by Stock Price Analysis (https://ieeexplore.ieee.org/document/9200116) 06/19 - 06/20

● Presented and published this paper at ComPE international IEEE conference. It proposes a way of obtaining Business Intelligence

(BI) by integrating concepts of Chaos Theory, Non-Deterministic Pushdown Automata (NPDA) and stock price movement.

● Defined factors affecting BI, formalised a system with NPDA, built a paradigm to inculcate multiple concepts, specified rules for state changes, and how to analyse results and make decisions.

● Provided a 7 step procedure on how it should be implemented using the stock price and the expected impact. EXTRACURRICULAR ACTIVITIES

● Bulls and Bears club member, Corporate Finance team, 09/22 - Present

● Certified Yoga Instructor, 05/22

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