Data Science
JASON AMITH FERNANDO
Phone: ------------
Address: 234, Harrison Avenue, Harrison, NJ -07029
Email: ------------
LinkedIn: ------------/in/jason-fernando-67058b20/
EDUCATION
New Jersey Institute of Technology, Newark, NJ, USA Anticipated graduation - Dec 2019
Master of Science, Data Science GPA: 3.83/4.0
Courses: Machine Learning, Big Data, Applied Statistics, Deep Learning, Data Structures and Algorithms, Database Management System Design, Data Analytics with R
Rajiv Gandhi Institute of Technology, University of Mumbai, Mumbai, India August 2009 - May 2013
Bachelor of Engineering, Instrumentation Engineering GPA: 3.53/4.0
SKILLS
Languages: SAP ABAP, Python, SQL, Java(J2SE)
Frameworks/Platforms: CUDA, Hadoop, MapReduce, SAP BOPF, SAP NetWeaver: ECC, Gateway, SAP HANA, AWS EC2
Libraries/APIs: Tensorflow, Keras
Version control: SAP CHARM, Git
OS: Windows, Linux, Unix
Database: MySQL, MSSQL, Oracle 12c.
Software packages/Tools: SAP CPM, PS, FI, CO, SD, CRM, C4C, Tableau, Weka, MySQL Workbench.
EXPERIENCE
IBM Dec 2014 - Jul 2018
SAP ABAP Developer/ Consultant
SAP.ABAP application development, enhancements and support: Worked with OOABAP, BOPF, BADIs, User Exits, Workflow, IDOCs, Adobe Forms, OData and SOAP services on modules such as SAP CPM 1.0, SAP PS, SAP C4C, SAP FI, SAP SD with ECC 6.0, EHP 12 on SAP NetWeaver 7.4. Developed reports, interfaces and enhancements for E&Y’s ERP system, in business modules of Finance, CRM and Commercial Project Management, from system Integration phase to support phase.
Electro Power Engineering Co. Aug 2013 - Oct 2014
Assistant Engineer
Worked on the Immediate Fire Fighting System, Instrument& Panel installation, field calibration, Process Instrumentation Diagrams and Interlock Wiring Schematics and got a brief exposure to SAP MM.
PROJECTS
Deep-Learning-NNs (Python) Jan 2019 - May 2019
------------/Jason-Amith/Deep-Learning-NNs.git
Implemented CUDA, OpenMP programs, Single layer neural network(SLNN) with sigmoid activation using Numpy, Stochaistic Gradient descent(SGD), Mini-batch SGD, SLNN training from scratch, convolutional neural network(CNN) on Mini-Imagenet, CNNs with transfer learning, to classify Kaggle datasets such as fruits-360, flowers and chest_xray. The constraint being 80% accuracy.
Rudimentary machine learning algorithms (Python) Oct 2018 - Dec 2018
------------/Jason-Amith/Rudimentary-Machine-Learning.git
This project is a collection of basic concepts in machine learning. Such as supervised learning algorithms, in Python. Some of the implemented classifiers are: Naive Bayes' Classifier, SVM and logistic discriminator, using datasets from the UCI machine learning repository, for training and validation. There's many more to come.
Discrimination of a single nucleotide polymorphism genotype dataset between case and controls (Python) Dec 2018
Implemented a model for classification of SNP data points into case and controls using SVM classifier and dimensionality reduction modules, from scikit-learn library.
Program Mercury (SAP ABAP) Dec 2014 - Jul 2018
Program Mercury is a worldwide replacement for Ernst& Young's Global Financial Information System and their Global Time and Expense Systems. Worked on OOABAP, BOPF, BADIs, OData and SOAP services, on modules such as SAP CPM 1.0, SAP PS, SAP C4C, SAP FI with ECC 6.0, EHP 12 on SAP NetWeaver 7.4. Implemented reports and interfaces and resolved defects during the following phases: build, system integration testing and user acceptance testing, pre-go live for Program Mercury.
JASON AMITH FERNANDO
Phone: ------------
Address: 234, Harrison Avenue, Harrison, NJ -07029
Email: ------------
LinkedIn: ------------/in/jason-fernando-67058b20/
EDUCATION
New Jersey Institute of Technology, Newark, NJ, USA Anticipated graduation - Dec 2019
Master of Science, Data Science GPA: 3.83/4.0
Courses: Machine Learning, Big Data, Applied Statistics, Deep Learning, Data Structures and Algorithms, Database Management System Design, Data Analytics with R
Rajiv Gandhi Institute of Technology, University of Mumbai, Mumbai, India August 2009 - May 2013
Bachelor of Engineering, Instrumentation Engineering GPA: 3.53/4.0
SKILLS
Languages: SAP ABAP, Python, SQL, Java(J2SE)
Frameworks/Platforms: CUDA, Hadoop, MapReduce, SAP BOPF, SAP NetWeaver: ECC, Gateway, SAP HANA, AWS EC2
Libraries/APIs: Tensorflow, Keras
Version control: SAP CHARM, Git
OS: Windows, Linux, Unix
Database: MySQL, MSSQL, Oracle 12c.
Software packages/Tools: SAP CPM, PS, FI, CO, SD, CRM, C4C, Tableau, Weka, MySQL Workbench.
EXPERIENCE
IBM Dec 2014 - Jul 2018
SAP ABAP Developer/ Consultant
SAP.ABAP application development, enhancements and support: Worked with OOABAP, BOPF, BADIs, User Exits, Workflow, IDOCs, Adobe Forms, OData and SOAP services on modules such as SAP CPM 1.0, SAP PS, SAP C4C, SAP FI, SAP SD with ECC 6.0, EHP 12 on SAP NetWeaver 7.4. Developed reports, interfaces and enhancements for E&Y’s ERP system, in business modules of Finance, CRM and Commercial Project Management, from system Integration phase to support phase.
Electro Power Engineering Co. Aug 2013 - Oct 2014
Assistant Engineer
Worked on the Immediate Fire Fighting System, Instrument& Panel installation, field calibration, Process Instrumentation Diagrams and Interlock Wiring Schematics and got a brief exposure to SAP MM.
PROJECTS
Deep-Learning-NNs (Python) Jan 2019 - May 2019
------------/Jason-Amith/Deep-Learning-NNs.git
Implemented CUDA, OpenMP programs, Single layer neural network(SLNN) with sigmoid activation using Numpy, Stochaistic Gradient descent(SGD), Mini-batch SGD, SLNN training from scratch, convolutional neural network(CNN) on Mini-Imagenet, CNNs with transfer learning, to classify Kaggle datasets such as fruits-360, flowers and chest_xray. The constraint being 80% accuracy.
Rudimentary machine learning algorithms (Python) Oct 2018 - Dec 2018
------------/Jason-Amith/Rudimentary-Machine-Learning.git
This project is a collection of basic concepts in machine learning. Such as supervised learning algorithms, in Python. Some of the implemented classifiers are: Naive Bayes' Classifier, SVM and logistic discriminator, using datasets from the UCI machine learning repository, for training and validation. There's many more to come.
Discrimination of a single nucleotide polymorphism genotype dataset between case and controls (Python) Dec 2018
Implemented a model for classification of SNP data points into case and controls using SVM classifier and dimensionality reduction modules, from scikit-learn library.
Program Mercury (SAP ABAP) Dec 2014 - Jul 2018
Program Mercury is a worldwide replacement for Ernst& Young's Global Financial Information System and their Global Time and Expense Systems. Worked on OOABAP, BOPF, BADIs, OData and SOAP services, on modules such as SAP CPM 1.0, SAP PS, SAP C4C, SAP FI with ECC 6.0, EHP 12 on SAP NetWeaver 7.4. Implemented reports and interfaces and resolved defects during the following phases: build, system integration testing and user acceptance testing, pre-go live for Program Mercury.