Hamid Rajaee
Data Scientist Iii @TD
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WORK HISTORY
Data Scientist Iii @TD
Toronto, ON, CA
Contribute to implementing MLOps-driven CI/CD pipelines for efficient model testing and deployment.• Generate impactful business insights through visualization, data mining, statistical analysis, and advanced machine learning techniques, driving strategic decisions and improvements.• Participate in the full-cycle development and deployment of end-to-end machine learning models, from data preprocessing to production integration.• Optimize transaction monitoring and risk-scoring models using Python, SQL, SAS, R, and Oracle (Oracle Financial Services Crime and Compliance Studio), enhancing customer behavior analysis.• Improve operational efficiency and compliance with statistical and data mining techniques, alongside machine learning models enhanced by explainability and bias/fairness assessments.• Conduct AML/ATF scenario performance simulation and tuning, playing a pivotal role in advancing machine learning initiatives. This included participation in Watch List Monitoring and NLP-based projects, initial threshold setting, and enhancing regulatory compliance and operational performance.• Participate in designing and implementing a predictive machine learning model for money laundering detection using MLOps principles.• Manage and deliver high-quality ad hoc projects on tight deadlines, conducting data mining to reveal hidden patterns and anomalies, enhancing risk management and operational strategies.• Support the bank’s initiatives against money laundering and terrorist financing risks by maintaining and enhancing transaction monitoring scenarios and analytical queries.• Present data-driven insights to stakeholders, driving strategic decisions and enhancing understanding of model impacts.• Establish and maintain a structured documentation process for scenario review programs, including writing Model Development Reports and meeting audit and regulatory requirements.
EDUCATION
Ferdowsi University of Mashhad
Bachelor's degree, Civil Engineering
Sharif University of Technology
Certificate, Data Science
Metro College of Technology
Advanced Diploma, Data Science
Azad University (IAU)
Bachelor's degree, Computer Science
George Brown Polytechnic
Certificate , Project Management
University of Arizona
Master's degree, Data Science
Sharif University of Technology
Master's degree, Geotechnical Engineering
ABOUT HAMID RAJAEE
MSc in Data Science from University of Arizona, with over 5 years of experience in data science, business analysis, and stakeholder management• Skilled in Python, Spark, R, SAS, SQL, VBA, Tableau, Power BI, Hadoop, Hive, Pig, HBase, Kafka, MongoDB, Big Data, ML, DL(ANN, CNN, RNN), NLP, Oracle, Azure, Databricks, AWS, and GCP.• Proven track record in utilizing a broad toolkit across Data Science, including the end-to-end lifecycle of machine learning models, NLP, and Big Data• Expert in extracting, visualizing, and manipulating data for hypothesis testing, statistical modeling, and predictive analytics, consistently delivering actionable business insights• Excellent take initiative, team player as well as independent achiever, adaptive, self-motivated, multi-task, detail-oriented, quick learner, and always enthusiastic to learn new technologies• Excellent experience in identifying needs, creating process improvement solutions, drawing out business insights, working with multiple stakeholders, and maintaining collaborative relationships with business partners• Strong proficiency in writing accurate, efficient, and complex SQL queries to extract and integrate data from multiple database sources• Excellent experience in using Tableau for creating customized dashboards and delivering business insights• Excellent experience in analytical programming such as Python, R, SAS, and Spark• Quantitative analysis experience, including handling, manipulating, and analyzing data, experimental design (A/B testing), and creating analytical reports• Expert in data preparation and preprocessing to reshape and refine the datasets into usable datasets• Experience with manipulating big data sets, filtering, and presenting large quantities of data• Strong analytical problem-solving and conceptual thinking skills• Ability to transform big data into business insights and actionable recommendations • Excellent experience in machine-learning concepts such as supervised and unsupervised learning, classification, regression modeling, time series analysis, multivariate analysis, cluster analysis, Logistic Regression, Decision Tree, KNN, Adaboost, XGboost, Random Forest, SVM, Neural Networks, Sequential, and Functional API • Profound ability to interface and coordinate project scopes in a fast-paced environment• Strong knowledge of statistics and experience using statistical packages for analyzing large datasets and creating analytical reports• Ability to identify predictive attributes of data sets and perform feature engineering to improve machine learning results
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