Hassaan Ali Khan
Melbourne,Australia
Summary
Data Scientist with 5 years of experience building AI-driven solutions that solve real business problems. My background spans forecasting, optimisation, automation, and decision-support systems, with hands-on experience across Python, SQL, Snowflake, BigQuery, GCP, and Power BI. Alongside traditional machine learning, I currently work with Anthropic Claude and Open AI Models, handling MCP connections and insight generation, along with AI-assisted business intelligence solutions. I enjoy turning complex data into practical solutions that improve decision-making and deliver measurable business outcomes.
Overview
4
4
years of professional experience
Work History
Data Scientist / System Optimisation Specialist
Wesfarmers Health (API)
Melbourne, Australia
03.2023 - Current
- Applied LLMs and prompt engineering techniques to enrich product data by extracting and standardising attributes such as form, pack size, strength, and product characteristics from unstructured descriptions.
- Developed prompt-based classification and information extraction approaches to transform inconsistent product descriptions into structured business attributes for reporting, modelling, and operational use.
- Introduced AI-driven store intelligence summaries using Copilot and Power Automate, providing planners with a consolidated view of store history, replenishment decisions, inventory trends, and operational context.
- Applied generative AI techniques to generate article-level insights and enrich product metadata, helping improve product understanding and supporting business decision-making.
- Leveraged Copilot, ChatGPT, and AI-assisted development tools to accelerate analytics delivery, streamline development workflows, and support rapid experimentation across forecasting, inventory, and product data initiatives.
- Led end-to-end delivery of SC2, a flagship data science project covering product substitution, demand modelling, and forecast automation for supply chain planning.
- Designed the product substitution framework using product attributes (active ingredient, drug strength, pack size, product group) and historical sales patterns to identify clinically and commercially valid substitutes.
- Built machine learning models in Python (classification achieving ~80% accuracy + regression) using rich feature engineering to predict correct substitutions and estimate optimal transfer quantities.
- Developed analytical workflows using SQL and Python across BigQuery and Snowflake, and maintained and updated BigQuery datasets for modelling, validation, and reporting.
- Took the solution from manual execution to production by designing and deploying Google Cloud Platform (GCP) Cloud Functions–based processes for daily automated operations.
- Developed a seasonality modelling framework to identify seasonal products and categories, enabling proactive planning and contributing to ~2% year-on-year availability improvement.
- Designed and implemented a new replenishment formula, optimising inventory holdings and delivering ~$30M in annual inventory savings.
- Consistently achieved end-of-month and end-of-year inventory targets through data-driven forecasting improvements and replenishment optimisation.
- Built and maintained Power BI dashboards for Inventory and Supply Chain teams, covering forecasting performance, inventory health, and end-to-end supply chain KPIs.
- Co-developed a Greenfield “what-if” simulation engine to test different forecasting, replenishment, and constraint scenarios and quantify outcomes before deployment.
- Enhanced forecast by optimising a Start-of-Month (SOM) forecasting logic to improve short-term forecast accuracy and stability.
- Established documentation, monitoring, and governance standards to ensure trust, transparency, and adoption of analytics-driven decision systems.
- Developed interactive analytics applications using Streamlit, including experience working with Streamlit in Snowflake environments to deliver business-facing insights and self-service reporting solutions.
Data Analyst
SILC Group
Australia
04.2022 - 07.2022
- Implemented automated data wrangling across hundreds of heterogeneous files.
- Designed a web scraping and classification interface for client data discovery.
- Developed Power BI dashboards to deliver personalised insights for business users.
Education
Master of Science - Data Science
Monash University
06.2021
Bachelor of Science - Eletrical Engineering
National University of Computer And Emerging Science
06.2017
Skills
- Proficient in Claude Opus & GPT Models
- Proficient in SQL and cloud-based databases
- Power BI and Tableau
- Machine learning frameworks
- GCP & AWS Cloud
- Skilled in GitHub for CI/CD
- Statistical analysis
- AI Engineering
- Experience with Connectors and MCP
- Time series analysis
- Advanced Usage of Snowflake
- Front-end JavaScript development
- Familiarity with Retrieval-Augmented Generation (RAG) Architectures
Timeline
Data Scientist / System Optimisation Specialist
Wesfarmers Health (API)
03.2023 - Current
Data Analyst
SILC Group
04.2022 - 07.2022
Master of Science - Data Science
Monash University
Bachelor of Science - Eletrical Engineering
National University of Computer And Emerging Science