• Wrote a data ingestion pipeline to clean and transform(docking, QSAR, molecular dynamics) molecular data into ML ready datasets. • Performed ligand-based virtual screening using DeepPurpose and Auto Dock on novel candidate drug molecules. • Built a POC web app with dashboard to monitor potential biomarkers using Python and Plotly

Bell | Dec 2021 - Mar 2022

Data Engineer

• Programmed, developed, and optimized databases daily using Teradata and SQL for the customer operations and marketing teams. • Defined objectives, scope, and KPIs with the requesting teams to develop or modify simple to moderate ETL streams. • Developed advanced SQL queries with multi-table joins, group functions, subqueries, and set operations.

Flexport | May 2021 - Jul 2021

Data Engineer

Built an ETL pipeline by restructuring and developing a legacy program into a POC. Migrated the entire POC codebase from python 2 to 3. Converted 15 Python scripts to Apache Airflow DAGs to automate the ETL process.

Walmart | Oct 2020 - Mar 2021

Data Analyst - Data Governance

Improved data integrity by working with cross-functional teams to bring over 1 million points of data to updated governance standards. Proactively monitored data accuracy by analyzing, cleansing, and validating large datasets. Successfully executed 100+ daily ad hoc data maintenance requests from across the organization

Loblaw Companies Limited | Nov 2019 - Oct 2020

Master Data Analyst

Wrote an ETL pipeline using Python to automate the process of sanitizing, transforming and sending emails to individuals with data relevant to them; cutting down 5-7 hours of manual work a week. Analyzed and identified gaps in enterprise data affecting digital and traditional sales using Python for more than 11 million transactions daily. Built dashboards identifying gaps in vendor data to support senior management decision making. Rewrote SAS automation scripts in Python and further automated the ETL process to cut down 30-45 minutes of daily manual work. Wrote complex SQL queries as part of an ETL pipelines using Teradata database and Python; speeding up daily data integrity tasks up to 50%.

SharpestMinds | Sep 2019 - Sep 2020

Data Science fellow

Building a full-stack machine learning application trained on the Tox21 dataset to predict environmental carcinogens using Scikit-learn, Flask, Bootstrap, and Microsoft Azure. Converted molecules to various binary fingerprints and trained logistic regression, knn and gradient boosting models - achieving a final accuracy of 96.4%.

Towards Data Science | May 2019 - Sep 2020

Writer and contributor

N/A

Cyclica | Apr 2019 - Nov 2019

Bioinformatics Data Analyst - Drug discovery team (co-op)

•Sanitized and collected information for over 17 million molecular compounds to create a private database removing the need to rely on commercial equivalents. •Built a pipeline written in python by utilizing Pandas, Numpy, and RDKit to perform molecular similarity searching • Created and maintained a database of 300 million rows using PostgreSQL to be used internally and possibly a platform feature. • Analyzed molecular data using various statistical measures to derive insight useful to industry partners. • Built and monitored indexes to bring down processing times from minutes to seconds to increase usability. • Wrote complex SQL queries using complex joins, grouping, aggregation, nested subqueries to pull specific records with greater efficiency. • Created Python scripts to pre-process and sanitize large data sets. • Utilized Google's Compute Engine virtual machine to build, perform machine learning tasks on, and query a large SQL database. • Integrated the ability to perform complex cheminformatics querying of a PostgreSQL database using RDKit. Cyclica is a Toronto-based, globally recognized biotechnology company that leverages artificial intelligence and computational biophysics to reshape the drug discovery process.

Bell | Nov 2017 - Aug 2018

Sales Representative

Serviced existing accounts and establishes new accounts by referring to price lists and product literature. Recommended changes in products and service to customers by evaluating competitive developments. Maintained professional and technical knowledge by attending educational workshops and establishing personal networks.

Robarts Research Institute | May 2016 - Jun 2017

Student Research Assistant

Thesis Project: Detecting Prostate Cancer Using Tumor-Activatable Minicircles Encoding the Secreted Biomarker SEAP Cell culturing and maintenance; mycoplasma testing- handling primary prostate cancer cells and normal control cells. Cell lines include various types of human and mouse derived prostate cancer. Production of Tumor-Activatable Minicircles - Major steps included transgene cloning, purification of Minicirlce DNA (mega and maxi prep DNA extraction kits). DNA extraction/isolation; PCR amplification; transformation, cloning, plasmid purification. Cell plating for invitro experiments - Transfected with jetPEI and other agents, measuring luciferase and SEAP activity with luminometer and respective kits. Used the following experimental procedures to collect data: Bioluminescence imaging of cells; Western blotting; BCA assays; Immunocytochemisty; PSA testing - ELISA kits.

My Education

Take a look at my formal education

Certificate, Artificial IntelligenceUniversity of Toronto | 2022

Master's degree, BioinformaticsUniversity of Guelph | 2019

Bachelor's degree, GeneticsWestern University | 2017

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