Dr. Silvia Carolina Mora Partiarroyo

-Provide technical expertise on how analytics & machine learning can help solve customer problems. -Development of mathematical models as part of a Condition Based Maintenance strategy. -Analysis of sensor, maintenance, & business data utilizing advanced data analysis techniques. -Develop processes and tools to monitor & analyze model performance and data quality. -In-region customer engagement, requirement definition & analysis. -Contribute to problem solutions regarding scope, schedule, & budget.

-Process and analyze manufacturing and business data to develop data cubes and reports according to customer requirements. -Consolidate project requirements across internal departments. Preparation of project schedules and status reports, monitoring of milestones. - Beta and acceptance testing of in-house financial software. -Contribute to the development of BI solutions (DWH, OLAP Cubes, Enterprise Management System, ERP). -Contribute to the implementation of BI projects (Data Governance, EMS, etc.)

-Designed and developed complex algorithms in Python to elucidate full-stack scientific problems (from evaluation and transformation of data to performing simulations). -Analysed and interpreted large datasets by applying statistical techniques and mathematical modelling. -Optimized in-house software by testing and debugging processes in order to validate operational requirements and improve user-friendliness.

-Conducted tutorials for postgraduate courses. Mentored Master’s students and provided one-on-one support to address academic queries. -Mediated between faculty and students to encourage dialogue, track feedback, and ensure a quick turnaround for students’ needs. -Improved course content by proposing enhancements and implementing suggested modifications.

- Programming for Data Science (using Python and R) - Data Mining (using Rapidminer) - Decision Support - Big Data - Machine Learning - Business Process & Big Data Use Cases - Advanced Statistics

Programming and simulations; Signal processing; Statistical analysis of large datasets; Data analytics; Wavelet and Fourier analysis; Atmospheric calibration of signals; Main tools/languages used: Python, Mathematica, Casapy, Latex

Data analysis; Scientific writing; Analysis of multi-frequency data; Scientific programming; Image/signal processing; Fourier analysis; Interferometry; Polarization studies of electromagnetic waves; Main tools/languages used: Python, AIPS, NOD3, Latex

Programming and modelling; Data visualization and analysis; Statistics; - Main tools/languages used: Matlab, C++, Fortran