AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Leadership - Data Science | Artificial Intelligence | MLOps | DataOps
• Accomplished hands-on builder - Data, Analytics & AI leader. • PhD in AI, 15+ years shipping products across 6 countries (EU & APAC). • Equally comfortable writing the code, architecting the system, and leading the team that scales it. • Experienced in leading highly technical Data Science, AI & Engineering teams • Cross industry experience in Healthcare, Transport, Internet, Telco, IoT, Startups and Public Sector orgs ⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊ Skillset: ⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊ ▪ GenAI / LLMs - LangChain, LlamaIndex, LangGraph, Claude Code, Hugging Face; RAG, agentic workflows, fine-tuning, LoRA / PEFT, FAISS, on-prem SLMs, NLP pipelines ▪ Knowledge & Semantic — knowledge graphs, ontology engineering, semantic web, graph analytics, SNA ▪ Python, R, SQL, Databricks, Snowflake, Git, Docker, CI/CD, ModelOps, Power BI ▪ Building high performance teams - fostering innovation and delivering measurable outcomes ▪ Analytics & AI - Strategy, Platforms and Ops ▪ End-to-end deployment of multiple enterprise AI solutions (Agentic AI Systems, LLM Product Development, Graph RAG) ▪ DataOps & MLOps ▪ Natural Language Processing ▪ Knowledge Representation and Reasoning - Semantic Web Technologies ▪ Cloud platforms, mostly Microsoft (Azure), Databricks & Snowflake ⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊ Publications: ⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊⚊ https://scholar.google.com/citations?user=4SAD7zcAAAAJ&hl=en
Johannes Kepler Universität Linz
Dr. techn. (PhD), AI & Informatics
January 1, 2013 – Present
Free University of Bozen-Bolzano
Joint Masters in Computational Logic (EMCL)
January 1, 2009 – Present
Vellore Institute of Technology
Bachelor in Technology (BTech.), Computer Science & Engineering
N/A – Present
Technische Universität Wien
Joint Masters in Computational Logic (EMCL)
N/A – Present
GovHack
Regional Lead for NSW
June 1, 2025 – Present
New South Wales, Australia · Hybrid
Cancer Institute NSW
Manager Data Science & Insights
January 1, 2025 – Present
Sydney, New South Wales, Australia · Hybrid
NZ Transport Agency Waka Kotahi
Head of Data Science
October 1, 2024 – January 1, 2025
NZ Transport Agency Waka Kotahi
Manager Advanced Analytics & Modelling
December 1, 2019 – October 1, 2024
NZ Transport Agency Waka Kotahi
Data Scientist, Tech Lead
November 1, 2018 – November 1, 2019
Domitila Technologies Limited
AI Engineering Lead & Co-Founder
March 1, 2017 – March 1, 2019
Auckland, Auckland, New Zealand
Wine-Searcher
Artificial Intelligence & Analytics Team Leader
August 1, 2016 – October 1, 2018
Auckland, Auckland, New Zealand
Inland Revenue NZ
Principal Advisor (Information Management)
May 1, 2015 – August 1, 2016
Auckland, Auckland, New Zealand
Inland Revenue NZ
Information Scientist
July 1, 2013 – April 1, 2015
Auckland, Auckland, New Zealand
The Telecommunications Research Center Vienna (FTW)
Researcher - (Big Data, IoT, Smart Homes, Marketing Automation)
December 1, 2009 – June 1, 2013
Vienna, Austria
Fondazione Bruno Kessler (FBK-irst)
Consultant Researcher (Natural Language Processing)
October 1, 2008 – September 1, 2009
Italy
IBM - Center for Advanced Studies (CAS)
Researcher (Contract)
June 1, 2008 – September 1, 2008
Rome, Latium, Italy
TU Dresden: Center for Information Services & High Performance Computing
R&D Intern - (Data Grid, Distributed Databases)
January 1, 2006 – April 1, 2006
Dresden, Saxony, Germany
OpenFridge
April 1, 2013 – Present
OpenFridge is a platform for collaborative collection and analysis of energy usage data from refrigerators in households and businesses. The goal of the OpenFridge initiative is to help understand the energy efficency performance of different types of refrigerators in the field in different usage scenarios, and in different physical configurations, and to support community in making decisions that can increase energy efficiency of the cooling service.
Introduction to AI Orchestration with LangChain and LlamaIndex
June 24, 2026 – Present
Databricks for Business Leaders
Databricks
June 24, 2026 – Present
Docker for Data Scientists
June 24, 2026 – Present
Data Analysis on Databricks
Databricks
June 24, 2026 – Present
Essentials of MLOps with Azure: 2 Databricks MLflow and MLflow Tracking
June 24, 2026 – Present
Essentials of MLOps with Azure: 1 Introduction
June 24, 2026 – Present
Electronics Foundations: Fundamentals
June 24, 2026 – Present
Azure Spark Databricks Essential Training
June 24, 2026 – Present
Data Science: Manage Your Team
June 24, 2026 – Present
Databricks Lakehouse Fundamentals
Databricks
June 24, 2026 – Present
Essentials of MLOps with Azure: 3 Spark MLflow Projects on Databricks
June 24, 2026 – Present
Tech Ethics: Avoiding Unintended Consequences
June 24, 2026 – Present
Machine Learning by Andrew Ng, Stanford University
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across government agencies (Cancer Institute NSW, NZ Transport Agency, Inland Revenue NZ), startups (Domitila Technologies), and research institutions (Johannes Kepler Universität Linz, FTW, FBK-irst, IBM, TU Dresden) demonstrates adaptability and a broad perspective. Involvement in initiatives like GovHack and OpenFridge suggests a commitment to community and open data, aligning with collaborative and innovative cultures. The breadth of skills and project types indicates a strong cultural fit for organizations valuing continuous learning and diverse problem-solving approaches.
Soft Skills & Operational Fit
The candidate's resume highlights strong soft skills such as Team Leadership, Coaching, Communication, Problem Solving, Critical Thinking, and Strategic Thinking. These are crucial for a senior Data Analyst role, especially in leading initiatives, mentoring junior team members, and effectively communicating insights to stakeholders. Experience with Agile Development, DataOps, and ModelOps indicates a good operational fit for modern data environments.