Digital Marketing Data

TEJA RAMESH DIWAN

LinkedIn ******@*****.*** +1-248-***-****

**** ********* *****, *** ***, Dearborn, MI 48126

EDUCATION

University of Michigan-Dearborn, MI, USA

Master of Science in Computer and Information Science

Current GPA : 3.78/4

BVBCET, Hubli, India

Bachelor of Engineering in Instrumentation Technology

GPA: 3.7/4

January 2020 - December 2021

September 2011 - May 2015

SUMMARY

Solution-oriented and hands-on utility player focused in software testing with additional experience in the start-up environment. Focused on creating collaborative efforts between support and engineering teams to implement system or product level changes to benefit end users. Worked in all stages of SDLC and STLC, expertise in building E2E scenarios that exercise operational and business workflow and automate the same. Experienced in Agile methodology to reduce defects and improve the quality of the product. Developed test plans and maintained them regularly. Experience in working with product owners, system analysts, developers to manage and provide oversight for deployment of releases into production environments. Expertise in Design of automated test frameworks and test suites for development and testing cycles. Proficiency in Digital Marketing and Data Warehouse, ETL, Big Data, Hadoop Architecture and Apache Spark, AWS, microservices Testing, BI Tools. Ability to learn quickly, often in high pressure situations, in order to fully understand and deliver new product, platform or any mixture of the two in stipulated time frame.

GRADUATE COURSES

1.Introduction to Big Data: Hadoop(Map Reduce) and spark framework, Shingling, Minhashing, Locality-sensitive Hashing, DGIM Bucketized Stream, Bloom Filters, Sampling streams, Recommendation systems, Content Based filtering, K-means clustering.

2.Advanced Operating Systems: Map Reduce,key-value store, Peer-to-Peer Distributed Hash Table. Scheduling, virtualization, MultiCast and Borrowing, RPC_Concurrency control, Time and Ordering.

3.Natural Language Processing:Text parsing and Preprocessing, Parts of speech tagging, Collocations, Word Sense Disambiguation, Text Summarization,Dialog Systems, Question Answering, Sentiment Analysis, Machine Translation.

4.Computer Network and Security: Buffer Overflow,Malware, Symmetric key crypto hash functions, Public key cryptography, Web Security, XSS attacks/Clickjacking, HTTPS TLS,Internet transport naming and routing.

5.Database Systems

6. Fundamentals of Program Management

PROFESSIONAL EXPERIENCE

iQuanti, Bangalore, India, Senior Quality Assurance Engineer

Nov 2018 – Oct 2019

Project 1: LQS: Link Qualifier Service

1.Participated in the design and development of software using Python and Django which led to increase in efficiency and speed of result prediction for SEO personnel

2.Developed test automation suites in Python Unit Test framework with database and API mocks, for multiple microservices

3.Developed new daily reports and enhanced existing reports in python that included PostgreSQL queries and MongoDB aggregations, for daily batch processes that run to fetch data from third party data providers

Project 2: Keyword Optimization

Description: ALPS is an in-house patented product. “Keyword optimization” being one of its features focuses on improving traffic to a website (client) driven by a data model which is based on the on-page content of the website.

1.Orchestrated the automation test execution plan for the entire feature. Automated the test scenarios using pyunit (Python Unit Test framework) framework

2.Involved in ETL process, for test data using AWS Redshift.

3.Performed Load testing for all microservices involved in KWO.

4.Involved in UI automation for this feature using Selenium WebDriver.

5.Earned “Outstanding achievement” award for “Bug Free Feature” in production environment.

Capillary Technologies, Bangalore, SDET Feb 2017 - Oct-2018

Project 1: ReON Essential insights

Description: REON an ETL tool on big data focused on omni-channel CRM analytics. Big Data acquired from the POS is stored in a master-slave machine of MY SQL, data from slave is then sqooped and an ETL is performed, resultant transformed data is persisted in respective AWS S3 bucket for the respective EC2- instance . The Big data cluster consisted of spark on top of Hadoop (Extract of the ETL). The ETL pipeline used Sqoop for importing data from MySQL transactional DBs (Transactional Layer). The transformations were controlled by a central metadata store which provided a template for each set transformation. These transformations grouped into pluggable modules were implemented on java and Scala (Load of ETL). The B.I ready data was pushed to AWS S3 buckets with spark over S3 setup.

1.Involved in test planning and test framework design .

2.Performed manual testing, the scope of which will encompass all functionality of modules to as a prequel to automation

3.Designed an automation framework for the data validation of Facts including Computed Measures & KPI's and Dimensions validations having Computed Dimensions for the transformed data.

Project 2: ReON- BIUI

Description: ReON BIUI essentially a BI tool based on the data served by the backend (ETL) . Query Server is an interface between spark and metadata. It constructs the query objects which is submitted to Nodejs and the processed result set is served to the BIUI for Data Analysis is performed to run the recommendation engine for various campaign purposes.

1.Involved in complete design and implementation of the test cases and solely carried out the entire E2E testing for all the features.

2.Designed an Automation test framework based on testNg for all meta API calls being fetched for query object .

3.Received Spot-Award Recognition for Regression Framework Designed for ReON- BIUI.

Infosys Technologies, Bangalore, India Systems Engineer Nov 2015– Dec 2016

Project – Gamification

Description: Gamification – is a web-based portal which follows a game for the defects raised throughout STLC. Game followed in Gamification was NFL. Software Testers get to log in the portal and raise defects and based on the severity of the defects raised, the team and the individual testers get certain points awarded. Earn / Loss of Points would be NFL based Terminologies.

1.Involved in Literature Survey of the game mechanics and Planning.

2.Involved in the UI development of the active screens of Gamification.

3.Received the “best debutant” award for extensive coverage of test scenarios.

SKILL SET

Programming Languages:

Databases:

Web Cloud based Technologies:

Tools:

Testing Frameworks:

OS:

C, C++, Java, Python, MATLAB

MySQL, PostgreSQL, Oracle SQL, MongoDB, Redis Cache, Spark-SQL

HTML, Django, AWS S3, AWS Snowflake, AWS RedShift, AWS EC2, Spark, Hadoop, DynamoDB, AWS EBS, AWS EMR

Visual Studio Code, Git, Jenkins

Junit, TestNg, Jmeter,pyUnit

Windows, Linux

ACADEMIC PROJECTS(GRADUATE)

Sustainability of restaurants based on location demographics:

Analyze the aspects that affect the growth of restaurants at different locations and to address questions regarding restaurant sustainability, by incorporating user preference functionality from various variables. This recommender system adopts a consumer preference paradigm and uses local restaurant knowledge to suggest the results. Feature Extraction, Tf -Idf is implemented based on content-based filtering. Clustering is implemented using k centroids. Regression Analysis is used to determine the statistical relationship between different variables.

Napster P2P FTS: This project is implemented in Java based on multithreading and socket principles using client-server architecture. Server indexes the contents of all peers who enroll with it and provides peers with a search tool. The server creates the peer index(Peer acts as both client and server).e. The user can select one of those peers and then the client connects to that peer and downloads the file. The peer as a server waits for requests from other peers and sends the requested file when requested.

Fake News Detection: This project develops a model to identify and classify fake news. Dataset LIAR is used to extract features to understand the accuracy of the model. The dataset is preprocessed using NLTK library and pandas .The data is classified into unigram, bigram, trigram and fourgram models from the train set to observe its performance on test set, 8 classifier algorithms their respective metrics(accuracy,recall,precision,F1-score) are used to evaluate the model.

Online Retail Management System: This project is being implemented on MySQL for management of the data of online Retail Management system. The database is designed by implementing the normalized schema, Stored Procedures and Triggers for the role of Admin and Customer, respectively. The UI for this system is designed using PhpMyAdmin.

Contact this candidate