Kanwar Singh

Machine Learning Engineer

Greater Toronto Area, Canada11 yrs 5 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in developing predictive models for financial services.
Proven track record in big data engineering and machine learning.
Strong mathematical background with a focus on data-driven solutions.

Stackforce AI infers this person is a Data Science and Machine Learning expert in the Fintech and Healthcare sectors.

Contact

kanwar33singh@gmail.com LinkedIn

Skills

Core Skills

Big Data EngineeringMachine LearningData ScienceAlgorithm DevelopmentDecision SciencePredictive Modeling

Other Skills

PythonScalaSparkMap reduceHiveImpalaSQLKafkaFeature EngineeringRC++OneTickEclipseTime Series AnalysisHadoop

About

Experienced Data Enthusiast with a demonstrated history of applying data engineering and machine learning algorithms for solving real world problems in various domains. I am skilled in Python, R, Statistics, Apache Spark, MongoDB, SQL, Data Analysis, C++, and SAS. I have experience in using and experimenting with wide spectrum of ML/AI algorithms in the field of management consulting, risk management, algorithmic trading and real estate to deliver robust data driven results. I am a Maths Graduate with strong machine learning and quantitative skills.I am interested in data science, predictive modelling, data mining and keen to be a part of a growing team. Building a mathematical model from empirical observations and seeing how my ideas perform, excites me.I am quick in learning new technologies/domains and quickly trying different ideas/tools to solve real world problems with concrete results.

Experience

11 yrs 5 mos

Total Experience

2 yrs 10 mos

Average Tenure

8 yrs 1 mo

Current Experience

Teranet inc.

Big Data Engineer

May 2018 – Present · 8 yrs 1 mo · Toronto, Canada Area

Involved in developing data pipelines using Spark and Map Reduce, streaming framework:Kafka and query tools - Hive, SQL, Impala which drives critical business decisions and provides streamlined data to various LOBs.
Reduced the data processing time by 70% using distributed computing.
Involved in feature engineering for Automated Valuation Model which is used by financial services institutions to reduce mortgage risks.
Skills: Python, Scala, Spark, Map reduce, Hive, Impala, SQL, Kafka, Machine Learning, Feature Engineering

PythonScalaSparkMap reduceHiveImpala+5

Estee

Senior Analyst ,Algorithms and Data Science

May 2017 – Feb 2018 · 9 mos

Develop mathematical predictive models using exchange's live market data to predict market movement.
Develop and implement algorithms for effective automated quoting in the stock exchange on the basis of the model predictions in the live market.
Research and integrate new frameworks and technologies - Remote Debugging, OneTick with the existing model development and implementation process.
Integrate code communications and multithreading.
Skills/Technologies- Python,R, C++, SQL, OneTick, Eclipse, Machine Learning, Time Series Analysis

PythonRC++SQLOneTickEclipse+4

American express

Analyst, Decision Science, US New Accounts

Dec 2015 – Apr 2017 · 1 yr 4 mos

Develop, evaluate, implement, track, and maintain predictive models for evaluating new applicant's risk and provide critical analytical support for business partners in Marketing and Strategy.
Partnered with the Big Data team to leverage Hadoop and machine learning algorithms into the existing model development framework so to calculate highly optimised and accurate model predictions.
Leverage machine learning techniques like Gradient Boosting Trees to predict income for new USA credit card applicants. Model used in production for verifying applicant's reported income.
Research and integrate new frameworks and databases with the existing model development process. Research third party data to compute new and powerful predictive features.
Develop reject inference model for predicting default rates of historically rejected applicants, a technique to reduce bias from the model.
Recommend optimal credit line to new credit card holders using machine learning techniques like kNN.
Skills/Technologies : Hadoop, Spark, SAS, Sql, R, Python, Machine Learning techniques like KNN, GBM, Statistical Inference, Classification

HadoopSparkSASSQLRPython+6

Axtria - ingenious insights

Associate- Data Science

Aug 2014 – Nov 2015 · 1 yr 3 mos

Developed promotion response models using nonlinear, diminishing returns methodology for predicting the impact able sales due to promotions in US demographics by a Japanese pharmaceutical.
Optimised the allocation of promotion budget across multiple channels using these response models and tested multiple scenarios for maximizing the profit.
Developed algorithms for extracting 20+ KPIs from large APLD data for delivering insights on patient purchase behaviour.
Worked closely with the client’s representatives for understanding their requirements and the timely delivery of the project.
Skills: R, Python, SQL, SAS, Feature Engineering, Regression, Clustering, Optimization Techniques

RPythonSQLSASFeature EngineeringRegression+4

Inria

Intern

May 2013 – Jul 2013 · 2 mos · Lille Area, France

Designed parallel semantics and syntax to be incorporated in the sequential language HIHOPE and the subsequent execution of its programmes on KALRAY procesor.

S&p global market intelligence

Intern

May 2012 – Jul 2012 · 2 mos

Facilitated auto extraction of data from financial filings/documents using spatial and coordinate analysis and designed and implemented an algorithm for the subsequent auto-linking.