Derryn Knife
Senior Analytics Developer at Shell Energy Australia
Brisbane City, Queensland, Australia
Summary
👤
Senior🎓
Top SchoolDerryn Knife is a Senior Analytics Developer with a decade of experience turning complex data, analytics, and ML problems into production-grade solutions across energy, mining, finance and SaaS. He designs and delivers end-to-end architectures on modern platforms (notably Databricks), guiding ingestion, feature engineering and model deployment for very large datasets while translating technical trade-offs into business outcomes. At Shell Energy Australia he pairs deep Python and ML development with stakeholder coaching to enable scalable, governed self-service analytics for trading teams. Previously he led high-impact projects at BHP that delivered multimillion-dollar revenue uplift and cost savings, and ran Reliafy as a director advising clients from POC to production. Trained in reliability engineering and philosophy, Derryn combines rigorous quantitative thinking with clear communication, often switching seamlessly between executive, business and deeply technical audiences.
10 years of coding experience
6 years of employment as a software developer
Master of Arts - MA Philosophy, Master of Arts - MA Philosophy at University of New England (AU)Diploma Military Leadership, Diploma Military Leadership at Royal Military College of Australia - DuntroonMaster of Engineering - MEng Reliability Engineering, Master of Engineering - MEng Reliability Engineering at University of MarylandUNSW Sydney
Github Skills (26)
algorithms10
scipy10
risk-analysis10
python10
survival-analysis10
weibull10
gamma10
distributions10
truncated10
reliability10
scientific-computing10
combinations10
survival9
reliability-engineering9
perf8
Programming languages (2)
Github contributions (5)
derrynknife/SurPyval
Dec 2018 - Jan 2023
A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.
Contributions:357 commits, 16 PRs, 294 pushes in 4 years 2 months
distributionspythonweibull-distributionoffsetsfit
derrynknife/RePyability
Apr 2016 - Dec 2022
Reliability Engineering Tools
Contributions:6 reviews, 62 commits, 13 PRs in 6 years 9 months
perfreliability-engineeringreliabilityengineeringtools-engineering
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