SUMMARY:

• Research Paper titled “ Co - movement between fixed income index and equity index” published in International Journal IJRCM, ISSN: 0976-2183 (Nov 2012)
• Find the period for peak of solar energy in north and south hemisphere and forecast the solar power in both hemispheres for 2012 to 2023 applying Machine Learning and FFT concept implemented with Python and Matlab
• Liquidity Risk and it Impact on equity market: An analysis in purview of high frequency trading. (Draft)
• Valued derivatives (American Options) using Monte Carlo simulation with Longstaff Schwartz algorithm
• Real time Pricing of Collateralized Debt Obligation, Collateral Mortgage Obligation. (In Process)
• Priced a convertible bond through binomial tree concept and analyzed the movement of delta for same
• Managed and analyzed movement of international portfolio consisting of two foreign ADRs and two U.S. stocks
• “An Empirical Study of International Fisher Effect”, Dec’11
• “ Contribution of ASEAN in development of South-East Asia” International Conference, Nov’09
• “Virtual Reality in Space Exploration Domain of Robotics” National Conference, Nov’07

COMPUTATIONAL SKILLS:

Database: WRDS, CRSP, COMPUSTAT, Yield Book

Statistical Software: Excel, Eviews, SAS Base, SAS Advance, SAS Enterprise Miner, Proc SQL

Programing Language: Python, Numpy, Scipy, Panda, Scikit, NLTK, Matplotlib, Java SE, Matlab

Technology: Machine Learning, Natural language Processing, Big Data, Hadoop, Numerical Analysis, Solution Architecture, Enterprise Architecture, Data Architecture, Data Modelling, TOGAF

WORK EXPERIENCE:

Data Scientist

Confidential

Responsibilities:

• Developed applications of Machine Learning, Statistical Analysis and Data Visualizations with challenging data Processing problems in finance domain.
• Worked in large scale database environment like Hadoop and MapReduce, with working mechanism of Hadoop clusters, nodes and Hadoop Distributed File System (HDFS).
• Worked with Big Data applications in Hadoop with HDFS, MapReduce, Mahout, Pig, Hive, HBase, Sqoop and Flume.
• Implemented machine learning and statistical concepts with Apache Spark.
• Read data from local files, XML files, excel files, JSON files in python with use of PANDAS module.
• Read from SQL DBs, Web through APIs and processed them for further use in python with PANDAS module.
• Performed subset, sort, reshape, merge, slice and edit on collected data with use of Numpy and Pandas module of python.
• Developed histogram, scatter, 3-D and other plots with use of different color combination in python with Matplotlib library of Python.
• Applied concepts of probability, distribution and statistical inference on given dataset to unearth interesting findings through use of comparison, T-test, F-test, R-squared, P-value etc.
• Applied linear regression, multiple regression, ordinary least square method, mean-variance, theory of large numbers, logistic regression, dummy variable, residuals, Poisson distribution, Bayes, naïve Bayes, fitting function etc to data with help of Scikit,Scipy, Numpy and Pandas module of Python.
• Develoed predictive models with help decision tree, Bagged Loess, Spline, bootstrap aggregation and Random Forest algorithms.
• Applied clustering algorithms i.e Hierarchial, K-means with help of Scikit and Scipy.
• Worked on Natural Language Processing with NLTK module of python for application development for automated customer response.
• Built and analyzed datasets using Python, SAS, Matlab and R (in decreasing order of usage).
• Applied linear regression in Python and SAS to understand the relationship between different attributes of dataset and causal relationship between them
• Conducted designed research on different product configurations and performed price-sensitivity analysis utilizing monte carlo simulation and random forest analysis on sample data.
• Evaluated demographic datafor use in the modeling process where credit baseddatawere unavailable (i.e. AlternativeDataStudies).
• Performs complex pattern recognition of financial time series data and forecast of returns through the ARMA and ARIMA models and exponential smoothening for multivariate time series data.
• Rigorous experience in Multivariate logit/probit models, Logistic models, Hidden Markov models and other Market research methods.
• Validated the Macro-Economic data (e.g. BlackRock, Moody’s etc.) and predictive analysis of world markets using key indicators in Python and machine learning concepts like regression, Boot strap Aggregation and Random Forest.
• Interfaced with large scale database system through an ETL server for data extraction and preparation.
• Identified patterns, data quality issues, and opportunities and leveraged insights by communicating opportunities with business partners.
• Delivered and communicated research results, recommendations, opportunities, and supporting technical designs to the managerial and executive teams, and implemented the techniques for priority projects.

Data Scientist

Confidential

Responsibilities:

• Developed applications of Machine Learning, Statistical Analysis and Data Visualizations with challenging data Processing problems in finance domain.
• Worked in large scale database environment like Hadoop and MapReduce, with working mechanism of Hadoop clusters, nodes and Hadoop Distributed File System (HDFS).
• Worked with Big Data applications in Hadoop with HDFS, MapReduce, Mahout, Pig, Hive, HBase, Sqoop and Flume.
• Read data from local files, XML files, excel files, JSON files in python with use of PANDAS module.
• Read from SQL DBs, Web through APIs and processed them for further use in python with PANDAS module.
• Performed subset, sort, reshape, merge, slice and edit on collected data with use of Numpy and Pandas module of python.
• Developed histogram, scatter, 3-D and other plots with use of different color combination in python with Matplotlib library of Python.
• Applied concepts of probability, distribution and statistical inference on given dataset to unearth interesting findings through use of comparison, T-test, F-test, R-squared, P-value etc.
• Applied linear regression, multiple regression, ordinary least square method, mean-variance, theory of large numbers, logistic regression, dummy variable, residuals, Poisson distribution, Bayes, naïve Bayes, fitting function etc to data with help of Scikit,Scipy, Numpy and Pandas module of Python.
• Develoed predictive models with help decision tree, Bagged Loess, Spline, bootstrap aggregation and Random Forest algorithms.
• Applied clustering algorithms i.e Hierarchial, K-means with help of Scikit and Scipy.
• Worked on Natural Language Processing with NLTK module of python for application development for automated customer response.
• Built and analyzed datasets using Python, SAS, Matlab and R (in decreasing order of usage).
• Worked in large scale database environment like Hadoop and MapReduce, with working mechanism of Hadoop clusters, nodes and Hadoop Distributed File System (HDFS).
• Interfaced with large scale database system through an ETL server for data extraction and preparation.
• Identified patterns, data quality issues, and opportunities and leveraged insights by communicating opportunities with business partners.
• Delivered and communicated research results, recommendations, opportunities, and supporting technical designs to the managerial and executive teams, and implemented the techniques for priority projects.

Confidential

Responsibilities:

• Performed quantitative analysis of co-movement between return on corporate bond index and treasuries of different maturities with value weighted stock index and equal weighted stock index.
• Performed in depth analysis of data & prepared weekly, monthly reports by using MS Excel.
• Deploying SAS scripts in SAS management console
• Quantitatively analyzed co-movement between return on high yield bonds of different grade and different maturities with value weighted and equal weighted stock index on time series data.
• Used SAS extensively for creating ad-hoc reports, match merge, append data validation, and data correction and cleansing.
• Implementation of Prediction models, Market Basket Analysis, Customer Segmentation and data analysis using SAS Enterprise Guide and SAS Enterprise Miner.
• Created Analytic reports including Charts, Pivot tables, and Compound layouts and assigned to specific dashboards.
• Created various kinds of reports anddashboardsto better understand the data.
• Wrote SQL Statements to extract Data from Tables to verify the output Data of the reports.
• Analyzed effect of liquidity crunch in current financial crisis by cross sectional study of change in yield of more than seventy different bond indices on time series data of 2005-2012

Manager - Credit Analytics

Confidential

Responsibilities:

• Led credit analysis team of four people in corporate banking branch
• Performed risk pricing, quantification of risk, credit proposal preparation for corporate clients
• Represented Confidential in proprietary software development for bank as subject matter expert
• Participated in JAD session, documentation of business case, BRD, FRD, test scenario, test cases.

Summer Intern

Confidential

Responsibilities:

• Developed in-depth working model and application of credit derivatives over the globe
• Compared the available Indian market instruments with Credit derivatives, OTC derivatives.
• Analyzed whether Indian market needs any credit derivative instrument
• Developed model for rural credit risk monitoring and mitigation

Data Scientist/Quant Analyst

Confidential

Responsibilities:

• Led business side in development of proprietary trading software for securities.
• Participated in preparation of Business Requirement Document, Functional requirement document, UAT.
• Devised long term trading strategies based on analysis of macroeconomic factors of different markets and sectors.
• Devised short and medium term trading strategies based on technical analysis of stocks and indices
• Correctly forecasted the easing of euro crisis based on political and economic factors and generated 25% ROI
• Correctly forecasted the alliance of top two aviation firms of Indian market and generated 22% ROI
• Performed valuation, fundamental analysis, balance sheet analysis, cash flow analysis of firms