Worked with a large global research and advisory firms to design and develop data platform including the architecture, prototyping and development of data extract, transformation, cleansing and integration of structured and unstructured data

Developed optimal design of data warehouse environments, analyzing complex distributed data deployments and making recommendations to optimize performance.

Transformed raw data into useful information and insights utilizing Analytics, Business Intelligence (BI) and visualization tools.

Developed intricate algorithms based on deep dive statistical analysis and predictive data modeling which deepened relationships, strengthened longevity and personalized interaction with customers; leading to a 25% increase in customer satisfaction and 16% increase in sales.

Updated the company's data warehousing techniques - data recall and segmentation, resulting in a 30% increase in usability for non-technical staff members.

Developed an ETS for data sources used for reporting by sales, inventory, and marketing departments and modernized the data streamlining processes, reducing redundancy by 25%.

Taught data science/full stack development/cyber security related courses such as Machine Learning , UML and R/Python programming.

Researched new techniques and strategies for teaching and presenting findings to other college professors within the institution.

Reviewed the curriculum currently in use by the university and updated it with current and emerging trends in the field of data science.

Successfully implemented loss minimization techniques that led to a positive overall loss reduction of 10% on monthly revenues.

Achieved a 14% month-on-month increase in revenue through the application of dynamic pricing techniques.

Located and defined two new process improvement opportunities that increased the company’s revenue by 15%.

Built statistical models using historical data to conduct customer-based pricing and constructed several predictive models, such as bad debt and churn models, resulting in a 20% lower churn and 8% lower high-risk debtors.

Developed prediction algorithms using advanced data mining algorithms to classify similar properties together to develop sub-markets; each zip code is divided into sub-markets using advanced data mining techniques.

Refined personalization algorithms for 400K customers on web and mobile, boosting engagement and time spent on the platform by 25%.

Solved complex business problems using Machine Learning techniques like Regression, Classification, Supervised and Unsupervised Recommenders; increasing team efficiency by 20% and reducing costs by 27%.

Performed market analysis to efficiently achieve business objectives; increasing sales by 34%.

Utilized web scraping techniques to extract and organize competitor data for evaluation.

Researched and analyzed political systems in various countries, developed and implemented (social) media strategic plans and political proposals for clients.

Used R to create a matrix of political, demographic and household data to develop a set of predictive models that applied a score to every voter.

Identified voters who would be positively influenced by ads, mailings, social media and other outreach efforts, which resulted in local political parties winning several municipal and provincial seats.