Data Scientist And Founder
CurrentNumeract: Data Science Driven by ExcellenceServices:- Advice / Consulting: explore the potential of Data Science projects, and explain and interpret findings- Data Processing: setup SQL and NoSQL databases, database architecture, ETL, data wrangling withefficient pipelines- Machine Learning: predict using Linear / Logistic Regression, Neural Networks, SVM, Keras / TensorFlow,Random Forests, etc.- Visualizations / Reports: graphs, interactive dashboards, PDF/Excel/Word reports, web presentations- Cloud / production deployment: turn key deployment using AWS, Spark, H2O, etc.- Mentoring and Training: use best practices, explain complex topicsProjects completed include:- Flexible R Pipelines with Caching- Running R on AWS Lambda- Identifying potential private equity investment opportunities using Machine Learning- Signal processing using Fourier Transform and Kalman Filter- Summary dashboard for Real Estate pricing data- Database setup and interface functions for financial data- Social Network Analysis of venture capital firms using D3.js graphs- Anomaly detection- Multi-country Clustering Analysis- Advanced portfolio optimization techniques including optimal rebalance and tax loss harvesting- Optimal use of limit orders using Reinforcement Learning- Multi-node multi-core R / Shiny- Logistic growth modeling- Pattern recognition in time series- Complex forecasting dashboard for an ethanol producerDetermine project scope, outcomes to measure, data to collect and the collection method. Given the project requirements, the analysis phase may include Econometrics techniques, Machine Learning / Deep Learning techniques and/or distributed processing using Spark. Once the analysis is completed, an automatic analytics tool can be built and deployed in production.
