Senior Data Scientist candidate in Toronto, Ontario, Canada

Summary

I have a strong academic background, having earned a bachelors degree in software engineering from IUST and a masters degree in knowledge management with multimedia from MMU Malaysia, where I worked on ontology-based content management systems as my master's thesis. Additionally, I completed various courses and workshops in data science and big data to expand my expertise.

I then pursued a Ph.D. in Computer Science with a specialization in Database Systems at UPM, where I conducted research on preference queries related to skyline queries over Dynamic and Incomplete databases. I have published multiple papers from my Ph.D. thesis in high-ranking conferences and journals.

Currently, I am a postdoctoral researcher at York University in Canada, where I am working on machine learning and NLP projects, as well as supervising master's and bachelor's students. I have also worked with various companies on data science and machine learning projects, beginning as a volunteer and trainer, then progressing to a senior data scientist consultant since 2014. I worked in different domains such as fintech, banking, healthcare, Airline, insurance, retail, and warehousing. I have experienced working with different technologies and software like Python, R, PySpark, Keras and more.

I lead an IoT, Machine Learning, and Big Data project as a consultant beginning in 2020. Additionally, I have received international certificates in Practical Machine Learning (John Hopkins University), Mining Massive Datasets (Stanford University), Process Mining (Eindhoven University), Hadoop (University of San Diego), MongoDB for DBAs (MongoDB Inc), and other data science certificates. As an HRDF-certified trainer, I have conducted various training and workshops (both online and in-person) to train data scientists.

Overall, I have over ten years of experience in various roles such as a lecturer or trainer for almost 7 years, database administrator, and data scientist for almost 9 years.

Expectations

As a data scientist or data analyst, there are several expectations I would have from my new job in the domain of data science and data analytics. These expectations include:

Meaningful Impact: I expect my work to have a significant and tangible impact on the organization. I want to contribute to solving complex problems, making data-driven decisions, and driving business growth through insights derived from data analysis.

Access to Quality Data: I look forward to having access to high-quality and diverse datasets that are relevant to the organization's goals. Working with clean, well-structured, and comprehensive data will enable me to perform accurate and insightful analysis, leading to valuable business insights.

Advanced Tools and Technologies: I expect to have access to state-of-the-art tools, software, and technologies commonly used in the field of data science and analytics. This includes programming languages (e.g., Python, R), statistical analysis packages, data visualization tools, and machine learning frameworks. Access to such tools will enhance my productivity and allow me to explore innovative approaches to problem-solving.

Collaborative Environment: I value collaboration and teamwork. I expect to work in an environment where I can collaborate with cross-functional teams, including other data scientists, analysts, domain experts, and stakeholders. This collaborative environment will enable me to learn from others, share insights, and collectively work towards common goals.

Continuous Learning and Growth: The field of data science and analytics is constantly evolving, and I expect my new job to provide opportunities for continuous learning and professional development. This could include attending conferences, workshops, or training sessions, as well as exploring new techniques, methodologies, and emerging technologies in the field.

Ethical and Responsible Data Use: I believe in conducting data analysis and utilizing data in an ethical and responsible manner. I expect my new job to prioritize privacy, data security, and comply with relevant regulations (such as GDPR or HIPAA) when working with sensitive or personal data. Maintaining a strong ethical foundation in data science is crucial for building trust and ensuring the responsible use of data.

Challenging and Diverse Projects: I am excited to tackle challenging and diverse projects that involve complex data analysis tasks, predictive modeling, and extracting actionable insights. The opportunity to work on a variety of projects across different domains and industries will keep me engaged and provide opportunities to broaden my skill set.

Overall, I expect my new job to offer a stimulating and rewarding environment, where I can leverage my data science and analytics skills to make meaningful contributions, continue learning, and grow professionally.