Summary
Overview
Work History
Education
Skills
Data Projects
References
Affiliations
Timeline
Generic

Mathi Vathanan

Melbourne,Australia

Summary

Highly skilled data science professional with experience in fast-paced helpline operations and regional education sectors. I recently assisted leadership in refining the National Autism Helpline (NDIS), focused on data integration, wrangling, and visual storytelling. I grew up in a regional town, Warrnambool, as a refugee and recipient of the Sir John Monash Humanitarian Scholarship, with a continuous learning mindset, and I have a passion for delivering real outcomes. I am passionate about bridging the gap between business and technology to enhance the organisation’s digital journey.

Overview

3
3
years of professional experience

Work History

Data Analyst Co-ordinator

Autism Connect - Amaze Inc
Richmond, Australia
10.2023 - 10.2024
  • Developed live dashboards for 200+ daily NDIS approved knowledge cases, complex data from Genesys, Salesforce, and Oracle DB into clear insights on case volumes, timelines, demographic trends, advisors' performance dashboard, reduced case resolution times since 2023
  • Executed the Hoodie Up data campaign with corporate partner Coles Group, generating 1,000+ engagements; collaborated with comms and exec teams to financial insights, donors' insights
  • Improved organisational compliance with NDIS reporting by training Autism Advisors on data entry processes, ensuring system adoption and increasing accuracy of client records for across operational

Data Analyst

Southwest TAFE
Warrnambool, Australia
02.2022 - 10.2023
  • Deployed real-time data pipelines to track over 20,000 fee transactions and forecast reports, integrating NAT, OTCD, and NCVER datasets with internal financial databases – automation
  • Collaborated with project leads to secure $1 million in state-of-the-art training equipment, aligning existing asset data with student survey responses, published evaluation to manager and government
  • Automated student dashboards, analyse course completion rates, socio-economic trends, and DEI insights, improving data-driven planning for institutional services and student support initiatives

Education

Bachelor of Applied Data Science & Science - Astrophysics & Mathematics

Monash University
School Of Physics And Astronomy

Skills

  • Power BI (DAX functions)
  • Python (NumPy, scikit-learn)
  • SQL queries
  • GitHub Actions CI/CD workflow
  • AWS Cloud retrieving and integration
  • Microsoft 365 tools (Excel, Outlook, and SharePoint)
  • Issue tracking
  • Documentation
  • Define requirements
  • Passion for continuously improving and learning new tools
  • Initiating tasks
  • Seeking feedback

Data Projects

  • DNA Variants Sequencing Analysis, Aimed to predict the likelihood of CHIP, a mutation based on patient's DNA make-up, Handled structural error, missing data, outliers, and sorting category variables in 1 million chromosome locations, Visualised and quantified variables through extensive exploratory data analysis, Validated a strong correlation between above 0.5 Allele frequency, chromosome loci and positive case, Selected most frequent 200 chromosomes locations (region-based analysis), I trained the > 0.6 AF and chromosomes in Random Forrest and accurately predicted the mutations with a success rate of 96%. (Taken a lot of optimisations), Delivered optimised model that can readily indicate the possibility of a patient chance of having CHIP mutation
  • Predicting the Age of a globular cluster, Observational research, Faculty of Astronomy & Astrophysics, Collected CCD images of a globular cluster with three astronomy students, Cleaned/reduced the noise in the raw science images by implementing shifting, scaling, and combining 500 images from various filters and applying flat field images., Heavy use of Python (astropy library), Taken all statistical measures mean, std, Poisson distribution to validate the consistency of photon counts and removing any hot pixels still there., Wrote code and modelled photometry, Compared with literature models (NASA archives)., Accurately predicted the cluster's age within ±2 million years, a high accuracy prediction, Delivered an end-to-end project management.

References

  • Emily Griffith, Monitoring and Evaluation Coordinator, Amaze Inc, emily.griffith@amaze.org.au, 0425 111 508
  • Kay Chong, Autism-Plus Program Coordinator, Amaze Inc, kay.chong@amaze.org.au, 0423 845 866

Affiliations

  • I enjoy sefse
  • heth

Timeline

Data Analyst Co-ordinator

Autism Connect - Amaze Inc
10.2023 - 10.2024

Data Analyst

Southwest TAFE
02.2022 - 10.2023

Bachelor of Applied Data Science & Science - Astrophysics & Mathematics

Monash University
Mathi Vathanan