Nina Bechis
Information Technology Developer
City of Edinburgh, Scotland, United Kingdom
Summary
👤
Senior🎓
Top SchoolNina Bechis is an Information Technology Developer with 10 years of experience specialising in WalkMe digital adoption solutions and SAP SPO support for enterprise clients. She designs and delivers in-app guidance that boosts user adoption, reduces support dependency, and streamlines complex workflows, working closely with consultants and solution leads from build through deployment. Her background in quantitative and qualitative research, statistical modelling and data visualisation (R, Python, jsPsych) gives her an edge in measuring impact and turning user behaviour data into actionable product improvements. Nina has contributed ML-focused example notebooks to the gpytorch repository, demonstrating practical hands-on skills with Gaussian Processes in PyTorch and an attention to code quality and reproducible examples. Based in Edinburgh, she combines consultancy experience, client-facing delivery, and operational roles—having also led cross-disciplinary project teams and frontline venue operations—so she’s comfortable translating stakeholder needs into reliable technical solutions. Certified in WalkMe Builder I & II, she brings both platform expertise and a researcher’s rigor to digital adoption projects.
10 years of coding experience
1 year of employment as a software developer
Master of Arts - MA English Language and Literature General, Master of Arts - MA English Language and Literature General at The University of EdinburghNational Senior Certificate, National Senior Certificate at Reddam House Constantia
Italian, English, Afrikaans, Portuguese
Github Skills (7)
mle10
pytorch10
machine-learning10
python10
ml10
gaussian-processes10
gpu-acceleration9
Programming languages (4)
Github contributions (5)
cornellius-gp/gpytorch
Jun 2019 - Oct 2019
A highly efficient implementation of Gaussian Processes in PyTorch
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 2 PRs, 7 comments in 3 months
Contributions summary:Nina primarily contributed to the example notebooks within the repository, specifically focusing on Gaussian Processes (GPs) implemented in PyTorch. Their contributions included adding new examples for latent function inference, rewriting and refactoring sampling methods from p(y|x), and fixing bugs related to existing code functionality. The code changes suggest a focus on enhancing and improving the utility of GPs within the framework, including code efficiency and semantics.
pytorchgpu-accelerationgaussianstochastic-processesmodular
NinelK/WavesProject
Oct 2017 - Dec 2020
Analyzing waves in heart using deep learning
Contributions:31 commits, 22 pushes, 5 branches in 3 years 2 months
analyzingpythoncaffe2deep-learningtorch
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