David Kotan Email & Phone Number

Chicago, IL, US

Mclean, Virginia, US

Stack: Java / Spring Boot, Docker, Helm, Kubernetes, AWS, Terraform, Jenkins, Elasticsearch, Twistlock, Sonarqube, Databricks, Spark

Chicago, IL, US

• Managed the teams responsible for the following areas: data science, QA, agile, data integration (ETL)
• Trained business analyst and QA leads in a test-driven SDLC and how best to capture business requirements.
• Involved in improving continuous integration framework.
• Trained and mentored team for business analysis, process engineering, risk management, optimization, and predictive analytics.
• Reviewed KPIs and architecture draft from data science projects, partnered with development team while moving to MVP. Examples: Rating engine, and planning engine
• Facilitated strategic efforts to merge three disparate distribution networks post-company spin via data and analysis efforts at multiple levels. Worked with business leaders in determining cost justification related to.

Chicago, Illinois, US

Chicago, Illinois, US

• Coordinated with business partners to navigate complex postal rules and manufacturing constraints for postage optimization platform, which drove significant growth in that department. Notably, was the key contributor.
• Demonstrated attention to detail and organizational skills when working with legacy applications, for server migrations or troubleshooting issues.
• Lead the data science team in creating predictive engine for truckload rates. Worked with business partners and offshore to build the software platform to utilize said engine. The model has won 1st place at the FMIC.
• Skills involved: agile development methodology, C#, ASP.Net, SQL, C++, R, Javascript, HTML, MATLAB, SSAS, SSIS, BizTalk, Azure ML Studio, Windows Server, Azure

Champaign, IL, US

• Theoretical Astrophysics and General Relativity
• Collaborated with student team, stepping into leadership role to visualize the result of supercomputer simulations for Black Hole - Neutron Star interactions.
• Managed large data sets and orchestrated several long-running processing events.
• Wrote in-house components for software renderer and interfacing the data sets in HDF5 format.
• Streamlined offline processing tools to better utilizing multi-threading and I/O wait times.
• Utilized fast fourier transform numerical techniques. The resulting frequency components were summarized in various contour plots over slices of our parameter space.