CV Jean FACK long uk.pdf



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Titre: Jean FACK
Auteur: Jean Fack

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Jean FACK
Developer IT C++ Finance
jean.fack@laposte.net
https://www.linkedin.com/in/jeanfack/
3 masters in Financial Market, Data Science et Machine Learning.
C++ (10 ans) - Python (1 an) - C# (2 ans) - Java (2 ans)
COMPETITION
CodeChef
Rating
Rank
Profile

1680 Elo (07/09/2022)
20941/236122 (top 9%)
https://www.codechef.com/users/jfack

Rating
Rank
Profile

CodeForces
1132 Elo (21/11/2022)
41903/129536 (top 33%)
https://codeforces.com/profile/jeanfack

Position
Letter
Position
Letter

2010
2004
2002
2001
2000
1999
1996
Proof

REFERENCE
Alexis BONNET
Responsable Summit IT World, HSBC-CIB
https://www.cv-pdf.fr/2022/10/05/recommandation-alexis-bonnet
Roland PORTAIT
Professor holder of the Chair of Finance
https://www.cv-pdf.fr/2022/10/05/recommandation-roland-portait
GRADUATE
Master Professional « Financial market option econometrics » – ESSEC/CNAM Paris
 1st on 71 students on examen: « rates products and portfolio management ».
Master Specialized « Business intelligence for bank and insurance » – ENST Brest
Master Research « Machine learning and decision » – UPMC Paris
Mastery in computer science – ULP Strasbourg
Licence in computer science – ULP Strasbourg
DEUG Mathématiques Computeur Science and Applications to Sciences – ULP Strasbourg
BAC Science option Mathématique – Jean de Pange High School Sarreguemines
https://www.cv-pdf.fr/2020/02/23/diplomes/

1/8

MathFi
Data Mining

Langage

Library

Software

FUNCTIONAL SKILL
Pricing : Linear and non-linear (B&S, Heston).
Simulation : binomial model CRR, Monté-carlo.
Classification : AFD, K-means, CART, C4.5, Khi2Merge.
Optimization : gradiant, simulated annealing, tabou search, evolutionnary algorithm, ants.
TECHNICAL SKILL
Imperatif : C++, C#, Java, Delphi, Rust.
Script : Python, Perl, VBA, bash/ksh, DOS, Powershell, Crystal.
Math : R, Gauss, Mathlab.
Make : GNU make, ant, Apache maven.
Functionnal : Caml, Prolog.
Meta : Lex/Yacc(Ocaml, Flex/Byson), LISP.
Database : relational (Oracle, Sybase, MySql, SQLite), graph (Neo4j).
Documentation : UML(Microsoft Visio), GraphViz, Latex, Doxygen, Sphinx.
Finance : Mysis Summit, Quantlib, Lexifi, 3VFinance Titan.
Data structure : STL, Boost, , xml(DOM, Xerces/SAX, xpath, JAXB), Hibernate.
Webservices : WPF/Winforms(C#), Spring(Java), Play(Java).
Parallelism shared memory : Windows thread (C++), Posix (Unix C), TPL (C#).
Parallelism distributed memory : Datasynapse (C++/Java).
Machine learning : Weka (C++), Pandas/numPy/scikit-learn (Python).
Optimization : IBM Cplex.
Middleware : Tibco rdv, IBM Websphère MQ, Corba.
Versionning : clearcase, Rational Team Concert, git, subversion.
Code analysis : AQTime, rational purify/quantify.
Continuous integration : Jenkins.
Cloud : heroku, aws, graphenedb.

2/8

EXPERIENCE
Banque de France
Mai 2020 - Fev 2022
http://www.banque-france.fr/
Paris - Place de la Bourse
Contract
Contractor Virtual Beehive Paris
Position
Developer C++/Python expert in optimization
Member of the Innovation Pole, attached to the SMOT (TARGET2/TARGET2SECURITY Project
Context
Management Service), development and maintenance of the MOM (Mathematical Optimization Module)
for T2S delivery settlement.
Getting started :
 Familiarity with MOM and analysis and simulation tools.
 Implementation of multi-currencies with the addition of DKK.
 Fixed a difficult multithreading bug that had been persistent for 2 years and was causing
instability in productions.

Task

IBM CPLEX version upgrade :
 Compilation upgrade.
 Upgrade of Cplex parameters.
 Fixed a difficult bug in the IBM CPLEX library settings that had persisted for several years and
was giving poor results in some tests.
 Improvement proposal :
 Separate data and their representations.
 Industrialize relevant data in SQL format.
 Improve architecture performance and maintenance.
Testing/delivery process:
 Automation of a game.
 Improved documentation.

Functionnal
Technology

Functional Evolution of MOM Reporting Web:
 IImplementation of formal specifications by Reverse Engineering of the legacy C# code for
importing MOM data.
 Evolution of formal specifications in collaboration with the client.
 Evolution of C# code.
 Optimization of a code which made it possible to go from 2h to 5mn for any date :
 Replace foreach+Array.Sort() by LINQ+OrderBy() which uses the stability property of sort.
 Implementation of a reconciliation in Python with pandas and numpy.
 Implementation of a reconciliation in SQL with SQLite.
 Improved SQL LDM (Logical Data Model) with 30% disk space reduction.
Settlement Delivery, TARGET2/TARGET2SECURITY.
Microsoft Visual Studio C++/C# Édition 2017, IBM z/OS XL C/C++ (Unix), librairie IBM CPLEX, scripts
ksh et cmd/Powershell, vba/Excel, SQL (SQLite), Pythons (Pandas, Numpy), Jenkins.

3/8

3VFinance - Viel Group
Oct 2015 - Juin 2017
http://www.3vfinance.com/
Paris-Place Vendôme
Contract
Intern
Position
Technical Leader C++
Context
Member of the development team of Titan ® Software , evolution and maintenance of the financial library.
Handover :
 Development on rate products.

Task

Functionnal
Technology

Refactoring and optimisation project (1 year) :
 Encapsulation of financials products (OOP).
 Migration of the data structure in Qt ®.
 Put in place Contract Programming (Design by Contract) Paradigm in critical section of code.
 Put in place best practices :
 Coding rule : Scott Meyers “Effective C++”, Herb Sutter “Exceptional C++”, etc.
 Agile Method : Robert C. Martin “Agile Software Developpement”, etc.
 Test Driven Development : Kent Beck “Test Driven Development”, etc.
 Put in place pré-computation.
 Parralelize computation with QtConcurrent.
 66 % reduction in treatment time of Titan ® Benchmark.
Derivative products, cash, Titan software.
C++ 14, Qt 5.7, AQTime, Git, Oracle, Jenkins.

Natixis AM
Dec 2014 – Sep 2015
http://www.nam.natixis.com
Paris-Quai d’Austerlitz
Contract
Contractor Sedona Paris
Position
IT Quant C#
Member of Data Pricing Model Services team, integrate the Lexifi ® library in Apollo software for
Context
sensitivity computation for vanilla rates products.
Handover on Lexifi library (https://www.lexifi.com) :
 Fonctionnal :
 Handover on the pricing models.
 Technical :
 Développement of sample in C#.

Task

Functionnal
Technology

Integration library in Natixis system :
 Fonctionnal :
 Lexifi configuration from Apollo (Editeur) and Apiload (Natixis homemade).
 Validation of models parameters with business.
 Comparaison with la librairie Fincad ® (http://www.fincad.com/ ).
 Documentation.
 Technical :
 Modélisation of architecture with GraphViz ®.
 Integration of library with framework Natixis in C# .NET 4.0.
 Continuous Intégration with teamcity ®.
 SQL-Sybase optimization for Apiload.
 LINQ .NET for Apollo system.
 Data Load on demande and cache system in C# for reduce query.
Pricing on vanilla products, Lexifi librairy, Apollo financial software.
C# .NET 4.0, LINQ, SQL-Sybase, Teamcity, Svn (Tortoise), Graphviz.

4/8

HSBC CIB
Dec 2009 - Nov 2013
http://www.hsbc.fr
Paris-Champ-Elysées
Contract
Contractor SII (Société Pour l'Informatique Industrielle) Paris
Position
IT Front C++
Member of Fixed Income Front Office IT team, around Summit ® (1,000,000 trades, 2000 users) and
Context
Datasynapse ® grid (2000 cpu), develop and support applications.
Development and support of real time mktdata feeding server of into Summit :
 Functionnal :
 Linear Interpolation of missing bucket on rates curves.
 Technical :
 Development and support of market data access Bloomberg / Reuters (C++/Java/C#).
 Development and support of direct market feeding from trader (spreadsheet VBA).
 Development and support of feeding server (C++/Java/TIBCO rdv).
 Development and support of web server (tomcat/spring MVC).
 Reafactoring of xml-object mapping with JAXB (Java).
 Configuration in Summit of new market data.

Task

Functionnal
Technology

Exportation of Swap, Exotic, Fra, Mm from Summit (C++) to Microgen (C#) with FpML format :
 Fonctionnal :
 défine FpML fields from Summit meta-model fields.
 Technical :
 C++ Summit stk API et Summit meta-model.
 Put in place real time trade feeding process Front to Back (C++ Summit stk API and must
API/webservice MQ/C# WPF).
 Reporting of trades characteristics and cashflows to Back.
Development and support around Summit pricing :
 Functionnal :
 Rate product pricing validation in Summit.
 Technical :
 Généralize rules using 5 différentes représentations into uniq table (Oracle).
 Générate décision tree using datamining algorithm C4.5 (weka API) .
 Simplify tree by introduce knowledge on data.
 Visualization/support of rules with GraphViz.
Rates products pricing, greeks, interpolation.
C++ (STL, Boost), C# (WPF), Java(spring MVC /JAXB), VBA , Python, dos, Summit(3.7, 5.2 FT, stk
API, must API, Orbix CORBA), DataSynapse 4.2, ORACLE 9.2, Websphere MQ, TIBCO rdv, Weka,
Graphviz, Clearcase, Rational Team Concert, Ctrl-M.

5/8

Crédit-agricole CIB
Mar 2006 - Nov 2009
http://ca-cib.fr
Paris-La Défense
Contract
Contractor SII (Société Pour l'Informatique Industrielle) Paris
Position
IT Risk C++
Member of Fixed Income Front Office IT team, around Summit, around Summit ® (400,000 trades, 1000
Context
users) and Datasynapse ® grid (400 cpu), develop and support applications.
Redesign computation chain of daily greeks and weekly Stress :
 Functionnal :
 Greeks configurations tables design.
 Stress tests design.
 Technical :
 Parallelism optimization using grid computing Datasynapse.
 Task optimization with automatized configuration table.
 Algorithmic optimization of task submission linear with data.
 Database contention optimization by aggregate result in memory.
 Network bandwith optimisation using binary sérialization of résultats.
 Code optimisation using STL/Multithreading Posix/ purify/quantify.
Task

Functionnal
Technology

Optimization of batch computation of daily VaR :
 Functionnal :
 Computation of historical VaR.
 Technical :
 Refactoring ksh scripts to remove loop.
 Redesign data logic model for remove temporary table/work.
 Optimization of query and index.
Put in place MtM on « gridded computation on demand » application QuickRisk :
 Functionnal :
 FRA and Bond pricing.
 Technical :
 Grid computing Datasynapse, Summit API.
Rates products, Greeks, Stress Tests, historical VaR, MtM.
C/C++/C#(Microsoft Studio, sunstudio, STL, Multithreading POSIX), Delphi 5.0(Borland), Java(Eclipse),
Perl, Python, ksh, Summit(v3.7, stk API, hedge API), DataSynapse 4.1, Sybase 12.0, dbx, rational
purify/quantify, Clearcase, Ctrl-M, crontab.

GL Trade - Sungard Group
Apr 2005 - Sep 2005
http://www.sungard.com
Paris - Place de la bourse
Contract
Contractor SII (Société Pour l'Informatique Industrielle) Paris
Position
Developer Engineer C++
Context
Member of IT team, develop and support trading software GL-Trade ®.
Modelization of implicit volatility on equity derivative :
 B & S formula reverse.
Task
 Dichotomy algorithm.
 Newton-Raphson algorithm.
Functionnal
Equity derivative, implicit volatility, Black Scholes reverse, numerical analysis, electronic trading.
Technology
C++(Microsoft Studio), win32 API, cvs.

6/8

Isoft
Apr 2004 - Sep 2004
http://www.isoft.fr
Paris - Saclay
Contract
Internship
Position
Machine learning specialist
Member of R&D team, put in place discretization tool in machine learning library of Data Morphing
Context
software Amadea ®.
State of the art of discretization :
 Supervised/not supervised.
 Uni/multidimensional.
 Bottom-up/top-down/incremental.
Task

Functionnal
Technology

Implémentation of unidimensional supervised algorithm
 khi2Merge.
Back testing :
 Class relevance.
 Stability to noise.
 Stability to data size.
Discretization algorithm, stress/back testing.
C++(Microsoft Studio), Isoft Amadea.

Dynamic Capital Management
Apr 2003 - Sep 2003
https://www.dynamicfunds.com
Paris - New York
Contract
Internship
Position
Machine learning specialist
Context
Member of R&D team, put in place optimization tool for tuning parameters of trading algorithm.
State of the art of multidimensional metaheuristic optimization algorithm :
 Simulated annealing.
 Tabou search algorithm.
 Evolutionary algorithm.

Task

Functionnal
Technology

Implementation of evolutionary algorithm with different possible representation dépending of input data :
 Symbolic : genetic algorithm.
 Numéric : strategic evolutionnary.
 Programmatic : genetic programming.
Back testing :
 Multidimensional polynomial function extrema problem.
 Traveling salesman problem.
 Food collection problem.
evolutionnary algorithm.
C++(Microsoft Studio), Delphi 5.0(Borland).

Artificial Intelligence Laboratory of Paris 5
Apr 2002 - Sep 2002
http://www.math-info.univ-paris5.fr/liap5-lab/liap5.html
Paris - Descartes University
Contract
Internship
Position
Machine learning specialist
Member of research team, Modelize compétition and coopération in plants. Compare Simulations résults
Context
with biological and ecological knownledge.
Functionnal
Modelization of competition / cooperation, collective intelligence, genetic of populations, evolution theory.
Technology
C++(Microsoft Studio), Delphi 5.0(Borland), moteur 3D ODE.

7/8

Image Science Laboratory of Strasbourg
Apr 2001 - Sep 2001
http://lsiit.u-strasbg.fr
Paris - Pasteur University
Contract
Internship
Position
Machine learning specialist
Member of research team, put in place time knownledge in classification hybrid algorithm of remote
Context
sensing image by take into account time information in images take at same position but with differente
date.
Functionnal
Classification algorithm, collective décision, time knownledge.
Technology
C++(gcc), CORBA.

Activities
Ultratrail
Ultratrail
Ultratrail
Triathlon
Cycling
Mountain
Danse

Description
Year
Ecotrail de Paris
2022
Ecotrail de Paris
2019
Ecotrail de Paris
2018
Triathlon de Paris
2017
Roc d'Azur
2017
Kilimandjaro
2017
Salsa - Bachata - Kizomba

ACTIVITY
Characteristic
80km - 1500D+80km - 1500D+80km - 1500D+1,5km - 40km - 10km
52km - 1200D+5895m

Time
12:50:30
12:37:12
12:19:34
03:07:24
02:40:05
5 days

Rank
Out of delay
1943/2006
1432/1738
1856/2320
2912/3605

"The value of a man lies in his ability to give and not in his ability to receive."
Albert Einstein

8/8




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