Binoy Dutt - https://www.linkedin.com/in/binoydutt

Email id: ac5ou2@r.postjobfree.com Mobile No.: +1-682-***-**** https://github.com/binoydutt

EDUCATIONAL QUALIFICATION:

MS - Information Systems (4.0/4.0) May – 2018

University of Texas at Arlington, Arlington, TX

(Business Statistics, OOPS, Data Mining, Data Science, DBMS, Project Management, Systems Analysis and Design, Big Data Analytics, Data Warehouse)

BS - Chemical Engineering (3.69/4.0) June - 2012

Nirma University, Gujarat, India

TECHNICAL SKILLS:

Tools: TABLEAU, HADOOP API, SPARK, SQOOP, FLUME, STATA, WEKA, HIVE, ECLIPSE IDE, SAS, MS PROJECT, MYSQL, MONGODB, QTP, HP QC, SELENIUM IDE, JMETER, MS OFFICE, POWER BI

Languages: Java, SQL, Python, R

Skills: Business Statistical Analysis, Big Data - Distributed Computing, Data Analysis, Data Visualization, Data Mining, Model Building using Sklearn, Machine Learning, Deep Learning, Natural Language Processing, Data Cleaning/Pre-Processing, Business Analytics, Systems Analysis and Design, Quality Assurance, Team Leading

PROFESSIONAL EXPERIENCE:

University of Texas at Arlington, Arlington, TX June -2017 – May - 2018

Role: Data Assistant - Experience on dealing with Prospective student’s data for UTA along with the Data pre-processing and cleaning and updating the People Soft Oracle DB portal.

Intellimedia Networks, Ahmedabad, India Sep-2015 – May - 2016

Role: Lead Quality Analyst - Experience in leading QA team. Worked upon improving processes and suggesting inputs upon key areas of challenges and implementing effective solutions. Introduced automation testing using Selenium.

Vibrant Enterprise, Ahmedabad, India Jan-2015 – Aug-2015

Role: Marketing Analyst - Understanding industrial client’s requirement and providing the suitable products bridging the gap between manufacturer and customers. Creating dashboards and report on sales and customer data which helped in targeting marketing.

Cognizant Technology Solutions, Pune, India Dec-2012 – Dec-2014

Role: User Acceptance Lead and Data Analyst- Experience in developing insights based on customer behavior data. Acquired Customer behavior data using web logs and replicated the same into usable formats. Playing a key role in the implementation of the project/initiative from a business prospective and commenting on the Go/No-Go decisions.

PROJECTS:

Death Records – Predictive Data Mining -Performing predictive analysis using WEKA for class variable Manner of Death using historical Death Records and making inferences based on the data set, using Machine learning models studying and interpreting the relations between significant attributes.

Statistical Analysis/Model Building - On Players data using SAS using linear Regression approach coming up with the best model based on various assumptions and criteria’s like R2 in predicting the Player Salary and performing Hypothesis testing (Annova, Chi- Square, Two way Annova).

Social Media Analytics – Collected tweets using twython, analyzed and developed insights implementing sentiment analysis using Textblob, WordCloud, Topic Modelling, summarization and keyword extraction using Genism and optimizing the result to gather location based insights – Python based

Pokemon GO Analytics – Data Collection of 11 variable using web scrapping on Google Play/App Store for 3 months at an interval of 10 mins. Analyzed the collected Dataframe using Scatter Plots and Co-relation coefficient. Compared best prediction model comparing Linear, Ridge, Lasso and Elastic Net regressions to predict future date values. Performed Deep Learning analysis to identify image tags using Tensor Flow – Python based

Resume Job Description Matching – Collecting data from Glass Door using selenium and performing resume parsing. Pre-processing the data using stemming, generating a similarity score using 300-dimensional vector space modelled using Deep Learning - Word2Vec and their TFIDF scores – Python based

Systems Analysis and Design – Based on One Stop solutions for student took the project through planning, analysis, and design phases of SDLC generating relevant diagrams and documents under each phase.

Big Data Project – Performed Predictive Machine learning project on Titanic Data set using Distributed Computing using Spark.

ACHIEVEMENTS:

Awards: High Flyer of the Month - 2011 Cognizant Technology Solutions, Certification of Appreciation – 2012 Lloyds Banking Group/Cognizant Technology Solutions.

Process Automation – At Intellimedia Networks which saved 8 hours of efforts per bug fix/release.

Streamed lined the project delivery - At Intellimedia Networks with increased documentation and processes allowing 30% increase in quality and overall productivity.

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