Parfait Munezero
Data Scientist
Stockholm
Summary
Data Scientist familiar with various tools for gathering, cleaning and visualizing data. Advanced understanding of statistical, mathematical and other analytical techniques. Highly organized, motivated and diligent with significant background in predictive, probabilistic modeling, clustering, classification and A/B testing tasks. Detail-oriented team player with strong ability to handle multiple projects simultaneously.
Overview
12
12
years of professional experience
12
12
years of post-secondary education
2
2
Languages
Work History
Data Scientist
Ericsson AB
Stockholm
05.2017 - Current
- Worked with software testers on various business cases in the aim of reducing human efforts in software testing.
- Worked with different data types such as log data (machine generated text), text, time series and events data.
- Created and implemented new predictive models to assess software quality and evaluate the root cause of poblems.
- Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets.
- Built and deployed A/B testing API for comparing memory usage profiles in baseline software and new software.
- Mentored data science intern on the project of computing similarity of text files using SBERT language model.
University Lecturer
Stockholm University
Stockholm
10.2014 - 12.2020
- Main lecturer of Bayesian learning at Masters level. Developed course's materials. Prepared and graded labs and final exam.
- Supervised different thesis projects on both master's and bachelor’s levels.
- Presented research findings in international conferences.
Education
Ph.D. - Statistics
Stockholm University
Stockholm 10.2014 - 12.2020
Master of Science - Statistcs And Data Mining
Linköping University
Linköping 08.2012 - 06.2014
Bachelor of Science - Applied Mathematics
University of Rwanda
Kigali 01.2007 - 03.2011
Skills
Data Mining
undefinedPublications
- Munezero, Parfait, Mattias Villani, and Robert Kohn. "Dynamic Mixture of Experts Models for Online Prediction." Technometrics (2022): 1-12.
- Munezero, Parfait. "Efficient particle smoothing for Bayesian inference in dynamic survival models." Computational Statistics 37.2 (2022): 975-994.
- Munezero, Parfait, and Gebrenegus Ghilagaber. "Dynamic Bayesian adjustment of anticipatory covariates in retrospective data: application to the effect of education on divorce risk." Journal of Applied Statistics 49.6 (2022): 1382-1401.
- Ghilagaber, Gebrenegus, and Parfait Munezero. "Bayesian change-point modelling of the effects of 3-points-for-a-win rule in football." Journal of Applied Statistics 47.2 (2020): 248-264.
- Munezero, Parfait, and Mattias Villani. "Generalized linear models with dynamic link functions." (2020). (To be submitted soon).
Work Availability
monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Quote
Your most unhappy customers are your greatest source of learning.
Bill Gates
Timeline
Data Scientist
Ericsson AB
05.2017 - Current
University Lecturer
Stockholm University
10.2014 - 12.2020
Ph.D. - Statistics
Stockholm University
10.2014 - 12.2020
Master of Science - Statistcs And Data Mining
Linköping University
08.2012 - 06.2014
Bachelor of Science - Applied Mathematics
University of Rwanda
01.2007 - 03.2011
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