Data Scientist / Machine Learning Engineer

I am a dedicated individual who welcomes change and accepts challenges, seeking opportunities for diverse experience and advancement within a growing team. Over the past three years, I have gained industry experience in generating insights from data, interpreting complex datasets, and presenting findings to senior management. My background includes working as a Scientific Officer with an electron microscopy group, where I analyzed elements using SEM.

I have hands-on experience building dashboards using Power BI and Google Data Studio, and I am well-versed in statistics, hypothesis testing, A/B testing, and experimental design. I have practical experience in building, training, evaluating, and optimizing machine learning models, with knowledge spanning time series analysis, regression, classification, clustering, deep learning, natural language processing (NLP), and generative AI.

I am proficient in Python, SQL, Pandas, Matplotlib, Seaborn, Scikit-Learn, and generative AI frameworks. Additionally, I am familiar with cloud platforms such as Google GCP, BigQuery, Airflow, and version control tools including GitLab and GitHub. I am an advanced user of MS PowerPoint, having created numerous presentations throughout my coursework and professional roles.

My responsibilities have included data analysis, drawing conclusions, and making recommendations for customer service units, including analysis of exercise bike data. I have experience extracting student data from Moodle discussion XML files, working with both qualitative and quantitative data, and developing ELT skills through extracting, loading, and transforming datasets.

I have collaborated on group projects at Athabasca University and Trios College, and served as an IT manager. I have drafted academic and scientific reports independently and within teams, managed task prioritization, and met deadlines in dynamic environments. I am skilled in planning and organizing tasks, collecting and validating information from multiple sources to achieve project objectives, and addressing challenges by developing alternative solutions and implementing business processes for customer service.