09/07/2022 updated
BA
100 % available
Sr Financial Trading Technologist
Edison, USA
USA
BEngg Computer Science 1st Class HonorsASP.NETJava (Programming Language)Microsoft ExcelApplication Programming Interfaces (APIs)AlgorithmsAmazon Web ServicesData AnalysisApache AntAutomationAWK (Programming Language)Big DataC Sharp (Programming Language)UnixC++ (Programming Language)Client Server Models
C++/C Stack, MS, C#, high performance distributed Grids in Production environment, Automated tools for testing, integration and global Production application deployment, Python 3.8/PANDAS1.3.1, Java/C++, PostgreSQL, Oracle, Microsoft VBA/Excel, C# Macros Programming, Pandas, Numpy, python, C++, state management, Rester API, Flask, Front End Desktop, Web, WPF, Winforms, WCF, java, databases, programming, API, Analytics, Python/C+ + /KDB, data structures, singleton, Algorithms, GUI, IBM MQ series, Machine Learning, Matlab, Python/ SWIG-C++/Object, Database, NET, Java// C++, RDBMS/HADOOP/Stats packages, Tibco RV, KDB, data analysis, data compression, memory mapping, Core Java, Python/C++/Oracle- SybaseRDBMS/HADOOP/Stats packages, open source, MCMC, C#/Oracle, Virtualization, C#/C++/Oracle technologies, vmware, Big Data, KDB/Q, C#/C++, scalability, C#/ C++, FI, C# /Excel, Front End, caching, Data Quality, Interface, Static Data, Java Pub/Sub Messaging Application, Oracle 9i Database, Java Native JNI Library, Oracle DB replication, Sybase 12.5, Stored Procedures, Sybase, 12.5 andOracle 9i, DB, XML, XSL, Oracle 9i, Servlets, MVC, IBM, Java RMI, JVM, Multithreading, JAR, Libs, Java Threads, Object Model, UML, Design patterns, MQ Series Interface, Summarizer Application, Java MQ Series, Apache ANT Tools, J2EE, IBM WSAD 5, J2EE Framework, Struts Application Library, Debugging, C/C++, Oracle 8i/8, HP-UX, UNIX, MS VB 5.0, Object Oriented, Roguewave, C++ Libraries, DB Tools, Oracle DB, C++ Compilers, WDB Debuggers, Object Oriented Analysis, Roguewave C++ Libraries, UNIX IPC Programming, Middleware, CORBA, IDL, Compilers, Java Client Server Objects, Oracle 8i JDBC Drivers, Visigenic, Oracle Database, ASP, AWS, Oracle 7.3.3, C, C/C++ Precompiler, PL/SQL, NCR UNIX Servers, Mainframe, Sun Solaris Client Server environment, DDL, DML, Database Migration, Oracle 7.3, Informix Online Dynamic Server, RDBMS, C Precompilers, PL/SQL Stored Packages, Scripts, Oracle 7.x Database Installation, Awk, Korn, Tuxedo ATMI, OLTP
Experience
Professional experience10+ years
Languages
EnglishGood
Project history
Development of Core Quartz Trade Processing modules for End of Day Processing, Risk Exposure and
Pricing Calculations using quant Libraries by capture of Deal , Instruments and positions
accurately using python,C++ swig extensions ,data acyclic graphs (DAG ) tweaking based on
bitemporal event state management and using Rester API, Flask for Snapping positions based on EOD
Markers for various asset classes Trading Desks as Commodities,FX,Equities,Fixed Income Bonds.
Design and Development of Front End Desktop and Web based Trading Applications using Microsoft
Technologies such as C#,WPF ,Winforms,WCF etc.
Pricing Calculations using quant Libraries by capture of Deal , Instruments and positions
accurately using python,C++ swig extensions ,data acyclic graphs (DAG ) tweaking based on
bitemporal event state management and using Rester API, Flask for Snapping positions based on EOD
Markers for various asset classes Trading Desks as Commodities,FX,Equities,Fixed Income Bonds.
Design and Development of Front End Desktop and Web based Trading Applications using Microsoft
Technologies such as C#,WPF ,Winforms,WCF etc.
Principal Achievements:
* Design,Development of Trading Systems and Strategies using mathematical probability based models
using opensource technologies as python/c++/java,oracle and postgresql databases.,asynchronous
event driven reactor based programming using network API etc.
* Automated Trading Strategies development and execution.
* Design,Development of Trading Systems and Strategies using mathematical probability based models
using opensource technologies as python/c++/java,oracle and postgresql databases.,asynchronous
event driven reactor based programming using network API etc.
* Automated Trading Strategies development and execution.
* Developed and Build the Real Time Muni Bond Trading System's various Modules of FICC Group used
by the traders in real time for computing VaR,PnL,Book Positions Inventory Management for
Bid/Offer to street using proprietary Volatility Risk Models before making crucial trading
decisions.It involved Real Time Pricing and various Yields (as YTC/YTM/Curr Yield/Nominal)
calculationto analyze Worst Callable Bond scenarios and analysis of Bond Analytics Greeks /Credit
Spreads(CS01) /Interest Rate Deriv Spreads and also Shock Analysis of +-1 basis points on Muni
and Corporate Bonds of various Styles(Fixed/Floater/Callable/Puttable) before making crucial
Trading Decisions which helped to increase revenue stream by 15-20% on single month.The
Technology Framework used was Twisted Asynchronous Reactor Deferred /Callback Eventbased
Programming using Python/C+ + /KDB/AMPS-NVFIX Messaging and prominent data structures and design
patterns as visitor,singleton etc.
* Developed the Algo Trading Modules by selecting implementation benchmarks based on
Liquidity,Arrival Price/ Volume,VWAP,backloading and frontloading adaptable market strategies and
using Smart Order Routing Algorithms, adapting based on Book Queue depth/Exchange liquidity for
max fills.
* Detected Race conditions which prevented refresh of Trading System GUI Controls and implemented a
Bitemporal Event State Layer to solve it.
* Developed Modules to get Real Time Market Data Feeds of US Treasury Yields using multiple Queues
of IBM MQ series product.
Perform muni bond portfolio analysis,backtesting,development of investing grade quant trading
strategies using AI /
Machine Learning/Matlab Decision Trees ,and development of Real Time Muni Bond Stream eTrading
System and
Risk management of Municipal Fixed Income Bond Portfolio products using latest/major technology
Stack(Python/
SWIG-C++/Object Oriented In Memory Database for real time trades/AMPS Messaging Server/ .NET and
Core Java// C++/Oraclesybase RDBMS/HADOOP/Stats packages ) employing best practices in all phases
in QUARTZ Platform of BofAML.Development of Risk Models and calibration/mark to market, end of day
yield curve /pnl etc.Implementing innovative solutions using Twisted Event Driven Reactor
Framework, Multithreaded and Asynchronous programmingusing Tibco RV /MQ Series
messaging,KDB-AMPS(Advanced Message Processing System) milliseconds/microseconds processing etc.
While working for Big Bulge Banks (BofaML,UBS ) Fixed Income trading desks,got a chance to work
with all major components of Trading Systems and KDB was one major component.The experience
involved working on common data analysis workflow consisting of :
* performing queries to extract meaningful time series trading datasets
* analyzing those Time Series records using powerful Q functions for VWAP etc analytics analysis
for Traders for best bid quote prices,executions etc.
* Solutions to coping with problems that big datasets introduce when it exceeds in memory and
disk of computer by configuring kdb to use partitioning and further partitioning to segmented
database.
* Scripts for data compression,memory mapping and access by multiple processes.
* administering of kdb servers using qcon command
* Other best practices employed as per suggestions/solutions to using different kdb/Q
components from first derivatives whitepaper series "Q for Gods"
* Developing event handlers for kdb+ processes using asynchronous event driver reactor based
callback servicing.
by the traders in real time for computing VaR,PnL,Book Positions Inventory Management for
Bid/Offer to street using proprietary Volatility Risk Models before making crucial trading
decisions.It involved Real Time Pricing and various Yields (as YTC/YTM/Curr Yield/Nominal)
calculationto analyze Worst Callable Bond scenarios and analysis of Bond Analytics Greeks /Credit
Spreads(CS01) /Interest Rate Deriv Spreads and also Shock Analysis of +-1 basis points on Muni
and Corporate Bonds of various Styles(Fixed/Floater/Callable/Puttable) before making crucial
Trading Decisions which helped to increase revenue stream by 15-20% on single month.The
Technology Framework used was Twisted Asynchronous Reactor Deferred /Callback Eventbased
Programming using Python/C+ + /KDB/AMPS-NVFIX Messaging and prominent data structures and design
patterns as visitor,singleton etc.
* Developed the Algo Trading Modules by selecting implementation benchmarks based on
Liquidity,Arrival Price/ Volume,VWAP,backloading and frontloading adaptable market strategies and
using Smart Order Routing Algorithms, adapting based on Book Queue depth/Exchange liquidity for
max fills.
* Detected Race conditions which prevented refresh of Trading System GUI Controls and implemented a
Bitemporal Event State Layer to solve it.
* Developed Modules to get Real Time Market Data Feeds of US Treasury Yields using multiple Queues
of IBM MQ series product.
Perform muni bond portfolio analysis,backtesting,development of investing grade quant trading
strategies using AI /
Machine Learning/Matlab Decision Trees ,and development of Real Time Muni Bond Stream eTrading
System and
Risk management of Municipal Fixed Income Bond Portfolio products using latest/major technology
Stack(Python/
SWIG-C++/Object Oriented In Memory Database for real time trades/AMPS Messaging Server/ .NET and
Core Java// C++/Oraclesybase RDBMS/HADOOP/Stats packages ) employing best practices in all phases
in QUARTZ Platform of BofAML.Development of Risk Models and calibration/mark to market, end of day
yield curve /pnl etc.Implementing innovative solutions using Twisted Event Driven Reactor
Framework, Multithreaded and Asynchronous programmingusing Tibco RV /MQ Series
messaging,KDB-AMPS(Advanced Message Processing System) milliseconds/microseconds processing etc.
While working for Big Bulge Banks (BofaML,UBS ) Fixed Income trading desks,got a chance to work
with all major components of Trading Systems and KDB was one major component.The experience
involved working on common data analysis workflow consisting of :
* performing queries to extract meaningful time series trading datasets
* analyzing those Time Series records using powerful Q functions for VWAP etc analytics analysis
for Traders for best bid quote prices,executions etc.
* Solutions to coping with problems that big datasets introduce when it exceeds in memory and
disk of computer by configuring kdb to use partitioning and further partitioning to segmented
database.
* Scripts for data compression,memory mapping and access by multiple processes.
* administering of kdb servers using qcon command
* Other best practices employed as per suggestions/solutions to using different kdb/Q
components from first derivatives whitepaper series "Q for Gods"
* Developing event handlers for kdb+ processes using asynchronous event driver reactor based
callback servicing.