As a data scientist, Peter Faase has expertise in solving complicated data problems and working with Big Data to generate useful insights, intelligence, and applications. Combining his strong communication, presentation, and analytical skills, he has created data-driven solutions for organizations by designing and running complex data analyses trajectories using machine learning, predictive analyses, Artificial Intelligence (AI), and other statistical and mathematical techniques. He is skilled with tools such as Python, MySQL, SPSS, and Excel and also familiar with Agile Scrum techniques.

Nicholas Lu is a goal-oriented engineer focused on ML systems and distributed architecture. He works across the MLOps lifecycle, building and maintaining data and model pipelines using Airflow, Spark, Kafka, and Kubernetes. His experience includes deploying containerised workloads with Docker, managing infrastructure via Terraform, and implementing CI/CD with Jenkins, GitLab, and Bitbucket Pipelines. He supports site reliability through monitoring, automation, and incident response in cloud environments (AWS, GCP, Azure, Alibaba Cloud). He codes in Python, Java, SQL, and Bash, and works extensively with Linux and open-source tools.

Sebastian is a Senior Data Science consultant with a background in industrial engineering, data science, and business administration, and more than 5 years of consultancy experience at top-tier consultancy firms (e.g. Deloitte) working for numerous Fortune-500 companies in various Data Science subjects such as Machine learning, MLOps, Natural language processing, finance analytics, M&A analytics, and satellite analytics. He is proficient in using different programming languages (e.g. Python, R, Java), and cloud environments (e.g. Azure, AWS, GCP). Lastly, he is also experienced in business skills such as coaching, project management, and stakeholder management.

Stephanie Mak is a highly experienced data and machine learning engineer with a strong track record of delivering data/ML projects, and enabling data-driven decision-making that aligns with business goals. She has also attained the DataBricks Certified Machine Learning Associate and DataBricks Certified Data Engineer Associate Certificates. Her latest work EnergyAustralia includes the design and delivery of DataBricks multi-workspace solutions for enterprise data lakehouse, data science laboratory, and ML engineering.