Data Scientist
Executive solutions
Total years of experience :2 years, 11 Months
Collaborated with General Management level executives to assess and agree on organizational data science and analytics needs. Screened potential candidates for technical competencies based on client needs, providing them with technical resource solutions.
Key achievements in the role:
Maintained 100% retention of services to clients through strong relationship building and a high quality of services provided throughout my tenure.
Managed and contributed to the placement of 10+ technical resources in alignment with identified company needs.
Converted raw files into parquet format and minimized storage. Analyzed, cleaned, and processed data. Generated visualizations for business-driven actions. Grouped and forecasted customer mortgage repayment behavior from demographics and repayment history. Trained new hires to operate with complex data sets. Evaluated statistical trends, patterns, errors, missing values, finding outliers, and distribution. Utilized Digital, ATM, and Branch channels to improve retail banking operational processes.
Key Achievements:
Delivered proof of concepts and minimal viable products.
Contributed to significant cost savings on advertising expenditures through research and Omnichannel Analytics; that determined specific target markets for particular products.
Created efficiencies in data analytics processes through the application of data mining techniques for data indexing and categorization.
Developed subject matter expertise on bank-wide, channel sourced transactional data.
Learned banking processes and data. Supplied ad-hoc insights employing data visualizations. Merged data with existing data sets. Documented data merges. Built key relationships with stakeholders.
Key Achievements:
Saved 50% of storage space by converting raw daily transactional bank data into parquet format.
Networked and communicated with project leads and senior business stakeholders.
Created insights on ATM usage, using transactional data with applied behavior analysis through machine learning techniques.
Explored, visualized, and transformed data. Completed Microsoft Professional Program for Data Science and ranked 2nd place in the graduating class.
Key Achievement:
Obtained 80% accuracy with Microsoft Azure for Capstone Project to predict student loan repayment in the United States.
Major in : • Modelling, Regression and Machine learning • Visual Data Analytics • Applied Data Analytics- tools, Practical Big Data, Data handling and Cloud distribution • Legal, Ethical and Security aspects of Data management
majored in statistics, computer science and mathematics