Worked as a senior developer on a variety of data science and AI engagements. Two core clients, the Australian Defence Force (ADF) and big four bank.Built programs leveraging data science, machine learning, data engineering, solution architecting and data engineering techniques. Most commonly used Python but also developed with SQL, SAS, PySpark and AWS suite. For my colleagues I co-led a course for the AWS Machine Learning Specialty certificate. Frequently my role involved… Show more Worked as a senior developer on a variety of data science and AI engagements. Two core clients, the Australian Defence Force (ADF) and big four bank.Built programs leveraging data science, machine learning, data engineering, solution architecting and data engineering techniques. Most commonly used Python but also developed with SQL, SAS, PySpark and AWS suite. For my colleagues I co-led a course for the AWS Machine Learning Specialty certificate. Frequently my role involved communication of technical concepts with non-technical stakeholders, capturing objectives, co-creating solutions and reporting on progress, outcomes and insights from data science applications.Project highlights include:- Established a novel AI capability for a department in the ADF and developed AI use cases- Built a credit risk evaluation system for a big four bank using data science and data engineering- Built an automated ETL and data migration platform with Snowflake, AWS Glue, S3, Step Functions, DynamoDB and Cloudwatch. Show less

Worked in a variety of data science roles for clients in financial services, telecommunications and public service.Built programs leveraging data science, machine learning, deep learning, natural language processing, transfer learning and data engineering techniques. Most commonly used Python, but also developed with SQL and R. Often represented the development team to present results and outputs to client business representatives.Project highlights include:- Data science… Show more Worked in a variety of data science roles for clients in financial services, telecommunications and public service.Built programs leveraging data science, machine learning, deep learning, natural language processing, transfer learning and data engineering techniques. Most commonly used Python, but also developed with SQL and R. Often represented the development team to present results and outputs to client business representatives.Project highlights include:- Data science, machine learning and data engineering for predictive analytics and anomaly detection at a top Australian telecommunications company- NLP, machine learning and deep learning to classify and escalate complaints at a Big Four bank- Built data science tools to execute remediation at scale for Big Four banks Show less

Responsibilities:- Implemented supervised and unsupervised machine learning models to solve forecasting, retention and marketing problems.- Performed data analytics on broad range of data, from government economic data to our client's member and interaction data.- Conducted interviews and focus groups to gain emotional, experiential and other qualitative information to form insight about consumers, businesses and the market.- Presented insights of our research directly to… Show more Responsibilities:- Implemented supervised and unsupervised machine learning models to solve forecasting, retention and marketing problems.- Performed data analytics on broad range of data, from government economic data to our client's member and interaction data.- Conducted interviews and focus groups to gain emotional, experiential and other qualitative information to form insight about consumers, businesses and the market.- Presented insights of our research directly to clients.- Managed an overseas team to meet client demands and deadlines. Show less