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VP AI and Data Science
■ More than 5 years of experience building AI and Advanced Data-Driven solutions in Equity Research and AI-powered quantitative strategies in Global Markets (Equities, Commodities, Rates, Fixed Income). ■ Proficient in leveraging Alternative Data across macro and equity sectors such as Nowcasting Macroeconomic Variables using Geospatial and Location Analysis. ■ Developed AI and LLM-based Trading Strategies based on news feed sentiment data. ■ Specialized in AI, Deep Learning, Machine Learning, Alternative Data Analysis, Statistical Modelling, Time Series Forecasting, Predictive Modelling in Finance and Healthcare. ■ People Manager, Team lead and mentor for data science professionals in capital markets. ■ Self-motivated, commitment to continuous learning, and enjoy working collaboratively in team environments. GitHub : https://github.com/omidbadr Google Scholar : scholar.google.com/citations?user=azPpZKcAAAAJ&hl=en
Ryerson University
Master of Science (M.Sc.), Electrical, Electronics and Communications Engineering
January 1, 2015 – June 1, 2017
University of Tehran
Bachelor of Applied Science (BASc) , Electrical and Electronics Engineering
January 1, 2010 – January 1, 2015
RBC Capital Markets
Data Science Vice President
November 1, 2023 – Present
RBC Capital Markets
Senior Research Data Scientist | Alternative Data
October 1, 2021 – November 1, 2023
RBC Capital Markets
Research Data Scientist | Alternative Data
September 1, 2018 – October 1, 2021
Sunnybrook
Data Scientist
January 1, 2018 – August 1, 2018
Toronto, Canada Area
Ryerson University
Mchine learning Researcher
September 1, 2015 – December 1, 2017
Greater Toronto Area, Canada
Ryerson University
Graduate Teaching Assistant
September 1, 2015 – August 1, 2017
Greater Toronto Area, Canada
Jam
Data Analyst
March 1, 2013 – November 1, 2014
Tehran Province, Iran
Master Thesis: Design and Implementation of Convolutional Networks in CT Scan Noise Reduction
September 1, 2016 – July 1, 2017
Applied Skills: Machine learning, Deep learning, Python, Tensorflow, SQL, CNN, Neural Networks, Statistical Analysis, Data Cleansing, Image Processing. In this project, I built a novel deep learning architecture, convolutional neural network and hierarchical feature extractor, to reduce the noise in CT scan images for lung cancer early detection. The framework presented end-to-end mapping solutions with no optimization task. The model outperformed state-of-the-art dictionary learning algorithms. Moreover, I Built a CT scan image database for big data analysis in Hierarchical Data Format.
Cultural Fit Analysis
The candidate demonstrates a strong fit for roles requiring innovation and research, evidenced by their master's thesis and research roles. Their experience in both academic research and a major financial institution (RBC Capital Markets) suggests adaptability to different work environments. The focus on AI-driven models and alternative data aligns with forward-thinking, data-centric cultures. The diversity of projects, from medical imaging to financial markets, indicates a broad interest in applying ML across various domains.
Soft Skills & Operational Fit
The candidate's experience as a Graduate Teaching Assistant and Machine Learning Researcher at Ryerson University, including supervising undergraduate students and leading brainstorming sessions, suggests strong communication, mentorship, and teamwork skills. Their progression through roles at RBC Capital Markets (Research Data Scientist to Data Science Vice President) indicates leadership potential and ability to handle increasing responsibility. The descriptions imply a structured approach to problem-solving and project management.