Applied Data Scientist / Technical Generalist

Product- and decision-focused, working end-to-end with messy data
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Work expectations

Status
Actively looking
Not looking
Open to new opportunities
Previously hired through SkillsRobin
Location
Melbourne
-
Open to relocating
Commitment
Full-time, Casual / Contract / Part-time, Join as a startup co-founder
Availability from time of offer
In 1 month or less
Experience
2-5 years
 experience
Top 3 programming languages/frameworks
Python, Shell/Bash, R
Also knows
TensorFlow, FastAPI, Git, Matplotlib, NumPy, Playwright, Pytest, scikit-learn
Preferred work environment
Hybrid, Fully remote, In the office
Strengths

I specialise in turning messy, real-world scientific or operational data into usable systems and decisions.
I’m strongest when the problem is under-defined: figuring out what matters, structuring the data, building the first end-to-end version, and iterating quickly based on feedback.
I work comfortably across data exploration, modelling, validation, and backend implementation, and I communicate well with both technical and domain experts.
I’m motivated by environments where progress is measured by outcomes and learning speed.

Interested in working involving

I’m looking for roles where machine learning and data are used to improve real decisions.
I’m most interested in early-stage or growing teams working with complex, messy data, especially in scientific, industrial, or technical domains, where I can build and iterate on end-to-end systems close to product and business needs.
While I’m particularly drawn to applied ML, scientific AI, computer vision, and data-heavy products, I’m very open to adjacent backend or systems work that enables faster learning and leverage.

Not interested in work involving

Other information
Able to work in Australia without visa sponsorship
Requires visa sponsorship to work in Australia

Pay expectations

Full-time
$
110000
per year
Casual / Contract
$
per hour
Pay is negotiable in exchange for equity
Pay is negotiable in exchange for equity
Pay is not negotiable in exchange for equity
Open to volunteering or working for equity only
Not interested in volunteering or working for equity only if joining as a co-founder

Referred by

  •  

Work experience

Proudest professional achievement
I built an end-to-end computer vision and ML system for automated contact-angle measurement during my PhD. The project involved collecting and cleaning noisy experimental data, generating synthetic datasets, designing training and validation pipelines, and running large-scale experiments on HPC infrastructure. The final system outperformed traditional analysis methods and was published in Langmuir. I’m proud of this work because it demonstrates my ability to take a poorly defined real-world problem, understand the underlying domain, and iteratively build a working system from first principles.

Software Tester / ML Developer — Early-Stage AI/ML Startup

2025 – Present

  • Automated API and web testing using PyTest, Requests, and Playwright.
  • Built NLP evaluation pipelines (POS tagging, confusion matrices) using Python and R.
  • Performed data analysis, model validation, and reproducibility improvements.
  • Gained hands-on exposure to AWS-based deployment and development environments.

PhD Researcher — Large Public Research University

2021 – 2025

  • Built end-to-end computer vision and machine learning systems for analysing physical and chemical data (contact angles, wetting, materials interfaces).
  • Designed synthetic datasets, validation workflows, and HPC-scale training pipelines.
  • Developed scientific Python tooling with OpenCV, TensorFlow, and related libraries.
  • Published research in Langmuir (ACS) and collaborated with chemists and materials scientists.
  • Led development of a desktop scientific imaging application in collaboration with computer science students.

Tutor & Research Assistant — Large Public Research University

2021 – 2024

  • Taught materials science and supervised Masters-level projects in ML and surface science.
  • Assisted in experimental analysis, modelling, and data-processing workflows.

Independent Developer — Personal Product Project

2025

  • Built an end-to-end application using Python, FastAPI, Streamlit, and automated data-ingestion pipelines.
  • Processed unstructured supplier data and delivered a functional UI for real users.
  • Demonstrated strong backend engineering, product development, and data pipeline capabilities.

Workshop Manager — Small Local Automotive Repair Business

2014 – 2022

  • Managed scheduling, quoting, and day-to-day operations in a fast-paced workshop environment.

Education

PhD in Chemical Engineering

University of Melbourne • 2021–2025

  • Thesis: Machine Learning and Automated Analysis for Contact Angle Measurement
  • Built ML systems for extracting structured scientific data from images
  • Developed synthetic datasets and HPC-scale training pipelines
  • Published in Langmuir (ACS Journal)
  • Developed open-source analysis tools using Python, OpenCV, TensorFlow, and PyTorch
  • Best Presentation Award, ACSSSC 2024

Bachelor of Science (Honours)

Monash University

  • Major in Chemistry, minor in Mathematics & Biochemistry
  • Honours thesis on ML prediction of molecular thermodynamic properties (HD 91)

International Research Experience

Leibniz-Institut für Polymerforschung, Dresden • 2019

  • Focus on experimental surface science and automated Python-based analysis tools

Leibniz-Institut für Oberflächenmodifizierung, Leipzig • 2024

  • Focus on experimental surface science and automated Python-based analysis tools
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