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Engineer Software Developer

Location:
Verdun, QC, Canada
Posted:
March 27, 2019

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Resume:

SAHIL SINGH SODHI ac8w9z@r.postjobfree.com • 514-***-**** • Github • LinkedIn

EDUCATION

**** - **** ********* ********** - ********, Canada Master of Applied Computer Science GPA 3.65/4.00 2012 - 2016 Vellore Institute of Technology - Vellore, India Bachelor of Technology in Computer Science GPA 8.35/10.00 OBJECTIVE

Seeking a Data Scientist / Machine Learning position, where I can utilize my analytical thinking and relevant expertise to help the organization, comprehend its long-term goals. Strong computer science background and plethora of experience using predictive modeling, data processing, and data mining algorithms to solve challenging business problems TECHNICAL SKILLS

Python, Scikit-Learn, Spark, Tensorflow, Keras, Numpy, Pandas, Matplotlib, Seaborn, Java, SQL, Algorithms, Data Structures, Design Patterns EXPERIENCE

Software Developer (JDA Software Pvt. Ltd., Banglore, India) [Jul 2016 - Jul 2018]

- Tools & Technologies worked with Java, SQL, Moca, Jenkins, JIRA, Apache Camel, Git

- Collaborated in agile Intelligent Fulfillment team for development of adapters for end to end integration and business workflows.

- Developed Request Generator to generate thousands of messages with dynamically populated data for a given workflow for Performance Scalability, and Reliability(PSR), and analysis of the interaction of JDA products with multiple users concurrently in real time.

- Worked on JDA RedPrairie Moca architecture (Service Oriented Architecture) framework in which warehouse, transportation management and many other JDA products are built.

PROJECTS

Prediction of Real Estate Property Prices, Source Code [Jan - Mar 2019]

- Developed a prediction model to remove dependency from appraisers to estimate current market value of asset, and conducted exploratory data analysis for feature selection and principal component analysis for dimensionality reduction.

- Built statistical model using random forests with adaptive, gradient and extreme gradient boosting algorithms, and implemented K-fold cross validation for measuring accuracies and grid search for parameter estimation.

- Created Ensemble Learning model by incorporating Hybrid Data- using Gaussian class conditional distributions along with feature engineering to achieve root mean logarithmic error of 0.121

Reducing Customer Churn for Bank and Financial Institutions, Source Code [Feb 2019]

- Implemented classification tools to model and predict churn based on customer’s credit score, tenure and geography for most valuable assets of organizations

- Deployed artificial neural networks, random forests, support vector machines, logistic regression, naive bayes and ensemble vote classifier with hyper-tuning the parameters using grid search

- Computed confusion matrix and AUC-ROC(Receiver Operating Characteristic) curves to determine accuracies of the models, and verified the best model with an accuracy of 86%

Classifying Articles of Clothing and Accessories, Source Code [Oct - Dec 2018]

- Model to improve the ability of machines to classify fashion items and accessories for 28x28 grayscale images with a label from 10 classes

- Developed convolution neural network model to classify images with reshaping and normalizing input data dimensions to achieve an accuracy of 91.96% after fine-tuning the parameters Recommender Model on MovieLens Dataset, Source Code [June 2018]

- Built recommender engine for MovieLens dataset using Spark to learn user preferences based on various factors like ratings, users and items

- Employed collaborative filtering (alternating least squares) with user and item biases with matrix factorization, and validated results to evaluate the accuracy of the recommendations and of the model

- Deployed code and test cases on Travis CI hosted at github RESEARCH PAPERS

Published in The International Conference on Inventive Computing and Informatics, Smart Chair an Internet of Things(IoT), IEEE Link [Nov 2017] REFERENCE

Kunwar Singh - SafeRide Health Full Stack Engineer 437-***-**** ac8w9z@r.postjobfree.com LinkedIn Nikhil Pawar - Amazon Business Intelligence Engineer 571-***-**** ac8w9z@r.postjobfree.com LinkedIn Jerry Punnoose - Outcome Health Business Analyst 716-***-**** ac8w9z@r.postjobfree.com LinkedIn



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