Skills
Python, R, SQL, SAS, Tableau, Apache Hadoop, Spark, Pig, Hive, PySpark, MapReduce, Django Tools RStudio, Anaconda - Jupyter, SAS Studio, SQL Developer Operating Systems & Scripting, Unix, Linux, Windows, Mac, Shell scripting, ANN models, Convolutional Neural Networks (CNN), VGG19, MobileNetV2, Image, tensorflow, Conv2D, R programming language, Apache Pig, Linux OS, NLP, data collection, machine learning, algorithm, Text mining, JSON, natural language processing, NER, Data analysis, Autosys, DB, backup, Unix shell scripting, ETL, SQL database, IBM, Python/SQL, matplotlib, seaborn, PLSQL, cursors, script, Unix platforms, error handling, shell script, DJANGO, VMWARE, Linux/Unix servers, nested queries, Oracle SQL Developer, Python/DJango, HTML, Agile, Nagios, Prisma Catia V5, Clear Case, ServiceNow, BMC Remedy, Cisco, Excel, Word, Power Point, HPSA, HP Server Automation, ClearQuest, WinSCP, Control-M, Actimize, Cron
Project history
09/2021
-
09/2021
Intern
Skillsize
Assisted the implementation and deployment of systems used for natural language input and
processing (NLP), data collection, machine learning model training, and deployment of machine
learning models.
* CV Content analysis: The project aim is to build an algorithm which identifies the job titles
along with the corresponding years of experience, company names with years of experience
* Data Collection: Gathered CV without multiple layouts as well as different file formats such
as .doc, .docx and .pdf.
* Text mining and cleaning: As the data is semi-structured, applied NLP which reads the text
from any type of semi or unstructured file and generates a structured JSON file. Identified and
removed the unusual, redundant texts by natural language processing (NLP).
* Model training: NER model with BERT is a powerful NLP model has trained to identify the
labels such as job_titles, company_names, dates and other along with following the IOB format.
* Results and performance improvement: Evaluations done using statistical techniques and
improved the model's performance by utilizing the python tools.
processing (NLP), data collection, machine learning model training, and deployment of machine
learning models.
* CV Content analysis: The project aim is to build an algorithm which identifies the job titles
along with the corresponding years of experience, company names with years of experience
* Data Collection: Gathered CV without multiple layouts as well as different file formats such
as .doc, .docx and .pdf.
* Text mining and cleaning: As the data is semi-structured, applied NLP which reads the text
from any type of semi or unstructured file and generates a structured JSON file. Identified and
removed the unusual, redundant texts by natural language processing (NLP).
* Model training: NER model with BERT is a powerful NLP model has trained to identify the
labels such as job_titles, company_names, dates and other along with following the IOB format.
* Results and performance improvement: Evaluations done using statistical techniques and
improved the model's performance by utilizing the python tools.
09/2019
-
02/2020
Technology Analyst
Infosys
Client: RBS, Banking Sector
* Data analysis: I resolved data issues by performing root cause analysis using SQL / Python.
* I was involved in modifying the code according to the client requirements and deployed in
production.
* I worked on Autosys, Prechecks, Postchecks, Bounce and Connectors check, WAS upgrade, DB
backup.
* Worked on design and development of Unix shell scripting as a part of the ETL process to
automate the process of loading.
* Worked on ETL tasks like pulling, pushing data from and too various servers.
* Implemented python and batch scripts to automate the ETL scripts runs every hour.
* Worked on CSV files while trying to get input from the SQL database.
* Data analysis: I resolved data issues by performing root cause analysis using SQL / Python.
* I was involved in modifying the code according to the client requirements and deployed in
production.
* I worked on Autosys, Prechecks, Postchecks, Bounce and Connectors check, WAS upgrade, DB
backup.
* Worked on design and development of Unix shell scripting as a part of the ETL process to
automate the process of loading.
* Worked on ETL tasks like pulling, pushing data from and too various servers.
* Implemented python and batch scripts to automate the ETL scripts runs every hour.
* Worked on CSV files while trying to get input from the SQL database.
08/2016
-
08/2019
Application Developer
IBM
Client 1: BMW, Automobile Sector
* Data analysis and data engineering according to the business requirements using Python/SQL.
* Data visualizations using matplotlib, seaborn generated to present to the project and
client-side managers.
* I Implemented the functions using PLSQL procedures, packages and cursors.
* Automated script in Linux and Unix platforms for error handling using shell script and I
received appreciation from the client-side manager for automating the daily manual tasks.
* Managed, developed a tool for customers and administrators using DJANGO, SQL and VMWARE
calls.
* Accessing the websites and fetch data for selected options using Beautiful Soup of python.
* Installation, configuration, integration, tuning, backup, crash recovery, upgrades, patching,
monitoring system performance in Linux/Unix servers.
* Data analysis and data engineering according to the business requirements using Python/SQL.
* Data visualizations using matplotlib, seaborn generated to present to the project and
client-side managers.
* I Implemented the functions using PLSQL procedures, packages and cursors.
* Automated script in Linux and Unix platforms for error handling using shell script and I
received appreciation from the client-side manager for automating the daily manual tasks.
* Managed, developed a tool for customers and administrators using DJANGO, SQL and VMWARE
calls.
* Accessing the websites and fetch data for selected options using Beautiful Soup of python.
* Installation, configuration, integration, tuning, backup, crash recovery, upgrades, patching,
monitoring system performance in Linux/Unix servers.
Local Availability
Available worldwide