I am a goal-driven and determined person, who is passionate about deriving data driven solutions to complex problems. I am very passionate about my work and consistent skill development. My experience extends to working as a data analyst during my tenure at Pick n Pay Ltd. I further augmented my skills with a Master of Science specializing in Data Science. I am experienced in machine learning, natural language processing for sentiment analysis, and image data analysis with deep learning models. Proficient in various programming languages, namely Python, Pyspark, R and SQL.
Developed dashboards using Excel for tracking participation and outcomes for university events; provided technology support to the Director of Operations and Event Managers; designed and published daily event boards using applications such as Trello, Zapier, Formstack and Social Tables; led trainings on Microsoft Excel for Conference Services staff, including pivot tables, power pivots and VBA.
Maintained database from external sources and monitored pricing against competitors in the market to ensure competitive price position; Performed statistical analysis on promotional activities to optimize stock picking and timing of promotions; Forecasted sales of upcoming promotion to ensure promotional activities are within budget; Worked with the Pricing Director and Merchandising Teams to understand pricing strategies and complete financial scenario analysis; Collaborated with aligned category teams to serve as main point of contact for pricing needs.
GPA: 3.97
Using SQL and Power Query in Excel, I developed a planning model to assist store managers to better predict product demand for promotional activity, resulting in 12% reduction in wastage in that category across 240 stores.
Using TensorFlow and Keras in Python, I designed and created deep layered neural networks to classify MRI images with the purpose of developing a tool to assist in the classification of patients with brain tumors.
Built pipelines using Apache Spark to ingest and analyze +1 million emails stored in a Hadoop database with the purpose of assisting a legal firm to statistically summarize text and algorithmically derive topics over time frames.
Sentiment analysis on tweets mined on various political campaigns, to understand public emotion of certain campaigns and area-based clustering of individuals and the main topics involved in conversations using Python.
Built deep layered neural networks to classify hand written digits utilizing Tensorflow-GPU.
Apart from being a data analyst, I enjoy playing soccer, volleyball and ultimate frisby during summer months. During winter, I am engaged in strategy games, board games and bowling.
I do enjoy staying up to date on the advancements in the machine learning and AI world and dabbling in new Python libraries (who doesn't right?).