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Vinay Sawant

 Software Engineer(Backend/Data Engineer/Data Science/ML/Go/Java)

EX-BookmyShow

•  City, MUMBAI IN  •  [email protected]

I have around 7+ years of experience as Software Engineer(Java/Python/Golang) by working into multiple technologies in Ecommerce and Fintech Domain.Experience with data engineering, machine learning, deep learning. Love to work on building backend/machine learning,data engineering in its entirety

GitHub : https://github.com/vinay10949

Contact No: +919769711499/ +917021334841

Motive & Profile 


Motive & Profile Go-getter, passionate about technology, innovation. Eager to utilize my technical skills combine with AI/ML domain knowledge and create practical products for the real world.Willing to develop values under company culture.

Skills

Programming Skills

7+ years of programming experience in languages like Java,Python,Golang. Experience on building BackEnd Systems,Microservices,Recommendation Engine, Loan Default Prediction Modules, SMS Profiling ,Fashion Recommendation etc using Data and Machine Learning.

Machine Learning skills

Sklearn,Numpy,Pandas,rapids,scipy, Keras, Tensorflow ,and Big data analysis skill with Python on multiple scenarios. Have attended few Kaggle competition

Technologies:

Python ,SQL,MySQL ,Golang ,Java , Spring , Hibernate ,Machine Learning ,Deep Learning ,Hadoop , Hive, Keras , Scikit-learn, Tableau ,Linux ,Redis ,NoSQL ,NLP ,Docker ,Computer Vision ,Rest/Grpc API ,Apache AirFlow, Git,Kubernetes,Queuing Systems like RabbitMq,Kafka,MongoDB

Cloud Platform:

Google Cloud Platform,AWS

Work Experience


SuperMoney (Software Engineer Backend,AI/ML/NLP ) June 2016 ~ Present

Built backend powered with microservices using rest/grpc apis .

Built complete backend. Built RealTime Notification Engine that powers customer reminder notifications for repayments and eligibility for new loan product. 

Built Calibrated ML model that predicts the probability of customer likely to default a short term loan. 

Built Computer Vision Module for identify aadhar and pan card, cheque and doing OCR on to Pan and aadhar. Also built scalable distributed systems.

Also built a simple SMS profiling using regex. 


Software Engineer (Bookmyshow Aug 2014 ~ May 2016)

Worked here as software engineer,worked in core team of building recommedation engine with low latency. Worked on building backend services. 

Worked on cold start problem of Music Recommendation Engine using audio features using vienna university library,then used machine learning to recommend music. 

Worked on bookmyshow realtime seat occupancy module that show real time seat occupancy on to bookmyshow app

BI Consultant (Team Computers-Mercedes) Aug 2013 ~ Feb 2014

Worked for client Mercedes ,helped them with building marketing dashboards in Qlikview

ML Projects

Document Detection using CNN

Developed a CNN model for identifying document types like PAN,AADHAR FRONT,AADHAR BACK,CHEQUE,
Was responsible for model training ,creation and deployment. 

CardioVascular Disease Detection(Hackathon May 2020)

Github: https://github.com/vinay10949/CVD 

Role- End to End Deployment,Testing,Monitoring,Retraining

Responsible Detailed EDA,Model Creation,deployment,testing of model,monitoring and retraining approach

Achieved Recall of 82% ,using F2 score as metric.

SmartBackGround Verification using Deep Learning,NLP and Computer Vision

Identifying eye descriptors and then calculated EAR I.e eye aspect ratio for consecutive frame to identify if person in frame is blinking his eyes or not

Built face verification module to verify profile photos with document photos.

Built name and address similarity between provided name and name in the document using combination of cosine similarity and Levenshtein Distance .

Short Term Loan Default Prediction 

Objective was to perform data engineering ,data pipeline and detailed analysis of our supermoney customers.

Also predict which first time Uber Customer is likely to default 5000 Rupee product loan. 

Achievement : achieved 0.79 F-Beta Score , loan default rate dropped by 40%.

 Predict Mercedes-Benz Greener Manufacturing Configuration Testing time (Kaggle)

Objective was to predict testing Time for various combination of congurations..This could be useful to priortize the congurations to be tested that could save most of our time. - Given a set of feature variables predict testing time. 

Github : https://github.com/vinay10949/AnalyticsAndML/tree/master/Kaggle/Mercedes-Benz_Greener_Manufacturing

Quora Question Pair Similarity (Kaggle)

Built a machine learning model to predict whether two questions asked on quora are similar or not . So that the similar questions asked may have the same answers which have been given earlier for the previously asked similar question.

Github : https://github.com/vinay10949/AnalyticsAndML/tree/master/Kaggle/quora-question-pairs

HomeDefaultCredit Risk(Kaggle 0.77 AUC)

Challenge was given various data like applicants- information about each loan application at Home Credit) bureau,we had to predict what is the application's capability to repay the loan.

Achievement : Was in top 30%


Github : https://github.com/vinay10949/AnalyticsAndML/tree/master/Kaggle/HomeCreditRisk

Fashion Outfit Recommendation based on Content Recommendation 2019

Used a pretrained Vgg16 model to extract visual features from outt , extracted text features from descriptions of outt like like weighted tdfword2vec

 Used combination of above features to nd the immediate neighbours tried both using Euclidean distance,and also trained LSH model above high dimensional of combined features to find immediate neighbours of outfit. 


Futher future ongoing work: Collecting fashion documents to train a word2vec on all fashion corpus documents like vogue etc, Convert a user text or query into a elements,style document query. Use outt as sequence of items and train a sequential model as recurrent networks, or graph Neural networks to solve problem like recommending an outt as sequence of items,or if any one item is changed new sequence should be considered.


Music Recommendation Engine(May 2016)

Created ML Recommendation engine for music,used Music Information Retrieval (MIR) from libary by Vienna university,used features like rhythm pattern,temporal descriptor,etc(approv 2000dimensions of one song) Used Locality Senstive Hashing algorithm +Episilon Greedy Approach for recommendation

Recommendation Engine based On History and Ratings (Dec 2014-July 2015)

Developed Timeband rules for users booking their events on BookMyShow,Developed system which recommended nearby venues,Also developed Recommendation system which used Movie Ratings to generate recommedations,Calculated Bayesian average of reviews to recommend top events (Movie,Plays and Concerts) in a region 

Technology : Python,Redis,MongoDB,Php 

Achievement Built one core component for Recommendation Engine with very low latency

Customer Segmentation depending on customers taste (Mar 2015)

Segmented the customers depending on customers taste ,as in genres,languages using Unsupervised learning using Spectral Co Clustering on to m aggregated dataset of users of transaction,ratings data.

.Validated the bicluster using consensus score

Customer Segmentation based on transaction history(Feb 2015)

Customer Segmentation based on transaction history (BigData) Feb-Mar 2015 Created a clusters of users based on their rules on transaction data, data was stored in MongoDB,user proles were over 10million docs,Users were classied as star user,active user,lapser,bouncer and OTB etc

BackEnd Developer Projects

Document Verification Service  (Sept2020 -Present)

Created Golang gRPC powered micro-service for extracting data from documents like Aadhar Pan,voterid using OCR.

Also created aadhar esigning document flow for signing documents via NSDL.

Smart Video KYC (July2020 -Present)

Created Golang gRPC powered micro-service for video kyc for Smart Background verification . Used protocal buffers 

and created grpc based Unary API. Designed High Level Architecture, written docker script and CI /CD Pipeline.


SuperMoney Entire Backend API (2016 -Present)

Created and handling entire backend for product called SuperMoney,the entire rest apis uses Spring Hibernate. Experience in Spring Framework such as Spring MVC. Strong hands - on experience with Spring IO, Spring Boot

SMS Parsing(2016 )

Created SMS proling application using regular expression and Named Entity Recoginition using python NLTK 


Golang GRPC Microservices for Project Management System (Freelancing) 2018

 Built robust grpc based microservices,built using Golanguage and GOA framework and developed corresponding test cases .

Client ResearchNow.


AscertLogger Microservices for AT&T(Freelancing)

Built an highly scalable logger service using Golang that can handle million writes per 10sec,used channels extensively,Wrote code for log rotation ,log compression .



Authentication services Freelancing July 2018 

Created Golang grcpc webservice that uses vault to run authentication service.Wrote service that creates users,assign roles,create certificates,authenticate using certificate etc

Client : F5



Event Notification Engine July 2017 

Built Golang webservice that uses GoogleCloud pub sub for creating Notication system Wrote GRPC based webservice in golang and created processor which listens to subscriber and sends notication to users. 

Role- Was responsible for creating and deployment of system into docker end to end. Was also partly responsible for High Level System Design

Client : Schlumberger



GPS Web Service  

 Built an logger service in Golang that can handle million writes of gps coordinates per 10sec,used channels extensively,Wrote code for detailed summary stats of gps coordinates like Distance travelled in a day ,

Which coordinate is likely to be his home.

Role- Was responsible for creating and deployment of system into docker end to end. Was also partly responsible for High Level System Design

Client : Supermoney



SeatOccupancy

Built a entire seat occupancy module that pinged 2500 cinemas by generated schedules,and capture the real time seat occupancy at that particular time ,all that information was stored in queuing system which was later consumed by SeatOccupancy engine that shows real time seat allocation in cinemas.

Also solved race conditions when concurrently many users were booking a seat which happened during peak season

Technology Nodejs,RabbitMQ,Mysql,Golang

Client : Bookmyshow



Education

Masters in Computer Applications 2010-2013 

Computer Science Major (Full Time)

Bachelors in Computer Science 2007-2010

Computer Science Major

Personal Details

DOB :25-08-1989

Birth Place :Mumbai.

Languages: English, Hindi and Marathi.

Marital status : Married

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