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Arina “Arisha” Rud Reporting & Health Analytics · Sydney
Arina “Arisha” Rud · NSW Healthcare & Government Reporting

Turning health and government data into clear, useful reports.

I am a finance and reporting professional now building my career in NSW health and government reporting. I use Excel, Power BI and SQL to create clear reports, check data, and explain the main findings in simple language.

View projects → Resume highlights
15+
Years finance & reporting experience
4
Tools: Excel · SQL · Power BI · Python
NSW
Health & government data
Tools
Excel SQL Power BI Python
Focus areas
NSW ED targets Elective surgery Access equity
Availability
Open to reporting, data quality & business support roles · Sydney · Hybrid / On-site
About

From finance reporting to health data.
Clear reports, careful work, useful insights.

Arina
📍Sydney, Australia
🎾Tennis coach & competitor
🎬Finance & film production background
🏥Transitioning into healthcare analytics

Hi, I'm Arina Rud — most people call me Arisha. I am a finance and reporting professional based in Sydney.

I worked for more than 15 years in finance and reporting in Moscow, including in film production. My work included financial reports, payment schedules, expense reports, management reports and documentation for senior leaders and investors.

After moving to Australia, I decided to build my skills in data analysis and health reporting. I am studying Excel, Power BI, SQL, basic statistics and Python. I am also creating portfolio projects using public NSW health data.

My goal is to work in a reporting analyst, data reporting, business support or project support role. I want to help teams make better decisions from accurate and well-organised data.

Outside of reporting, I work as a tennis coach. This has helped me build confidence in communication, patience and explaining ideas clearly.

📊
Finance and reporting experience More than 15 years preparing financial, operational and management reports.
🔍
Careful data checking Focused on accuracy, clean documentation and checking information before reports are shared.
💬
Clear communication Experienced working with managers, investors, employees, vendors and contractors.
Resume

Skills & experience.

↓ Download Reporting Resume↓ Download Support Resume

Skills snapshot

Excel Advanced
SQL Beginner / Developing
Power BI Intermediate / Developing
Python Beginner
KPI design Stakeholder reporting Clear writing

Experience

Finance & Reporting Manager
Kinocompania / Russkoe Kino · Moscow · 2006–2022
  • Prepared production progress, expense, payment schedule and management reports for senior leaders, executive producers and investors.
  • Established a reporting system adopted across the company, improving consistency and visibility of project and payment reporting.
  • Maintained accurate financial documentation across payroll support, payment processing, banking, budgeting and accounts payable/receivable.
Management reporting Financial documentation Stakeholder communication
Projects

Health data portfolio projects.

Each project shows the question, data source, analysis steps, main findings and next questions.

Project 01 Portfolio case study

NSW ED Target Performance — Metro vs Regional

A practice project using NSW health-style performance measures. It compares metro and regional results, checks the data, and summarises the main changes over time.

−4.7 pp
Metro 4-hr discharge
Jan–Mar → Jul–Sep
−3.1 pp
Regional 4-hr discharge
same period
30%
Admit/transfer
within 6 hrs (Jul–Sep)
Excel KPI reporting Time trends
Read case study →
Project 02 In progress

Elective Surgery — Wait Times & Recovery

A planned project looking at waitlist changes across NSW health services, using SQL and Excel summaries.

SQL Excel
Coming soon
Project 03 In progress

Hospital in the Home — Adoption & Outcomes

A planned Power BI project showing service activity and differences across Local Health Districts.

Power BI Dashboard
Coming soon
Project 04 In progress

First 2000 Days — Equity Snapshot

A planned project looking at early childhood health indicators and differences by area.

Power BI Equity reporting
Coming soon
Project 05 Planned

Regional Access Capstone — What Drives Differences?

A final project combining results from the earlier projects to look at metro and regional differences.

SQL Power BI Storytelling
Coming soon
Contact

Let's connect.

I'm actively looking for reporting analyst, data reporting, data quality, business support and project support roles in NSW health, government or data-driven organisations. If you're a recruiter or hiring manager, I'd love to chat about how my finance reporting background and portfolio projects align with what your team needs.

Based in Sydney · Available for hybrid or on-site roles

✉
rudarina@gmail.com
Email
↗
in
linkedin.com/in/arina-rud-49a9b912b
LinkedIn
↗
git
GitHub profile coming soon
GitHub
↗
© Arina “Arisha” Rud · NSW health & government reporting
Last updated
← Projects / ED Target Performance
Portfolio case study Project 01

NSW ED Target Performance
Metro vs Regional Portfolio Case Study

Practice question: How is NSW ED within-target performance changing over time, and how do metro and regional results compare?

Excel KPI definitions Trend analysis Metro vs Regional
↓ Workbook coming soon ↗ GitHub coming soon
−4.7 pp
Metro discharge within 4 hrs
Jan–Mar → Jul–Sep 2025
−3.1 pp
Regional discharge within 4 hrs
same period
30.0%
Admit/transfer within 6 hrs
Jul–Sep 2025

Key findings

The project compares metro and regional performance over time. It looks at which measures are improving or declining, and where results may need more detailed review.

Interpretation: Some measures appear weaker than others. This may point to patient flow or capacity issues, but more data would be needed before making a final conclusion.

Data & definitions

Source: Public NSW health performance reporting / portfolio dataset notes. All metrics are reported as % within target.

  • Discharged within 4 hours: % of ED presentations discharged within 4 hours.
  • SSU within 4 hours: % admitted to ED short stay unit within 4 hours.
  • Admit/transfer within 6 hours: % admitted to hospital or transferred within 6 hours.
  • 12 hours or less: % with total ED time ≤ 12 hours.

Data checks

  • Checked for missing values and percentage values outside the 0–100% range.
  • Checked the metro and regional groupings used in the analysis.
  • Checked date ordering and percentage-point change calculations.
  • Noted any incomplete or unclear data in a QA log.

Visual outputs

📊 Chart placeholder — replace with exported image <img src="assets/ed-line-chart.png" alt="Metro vs Regional discharge within 4 hours" style="width:100%; border-radius:10px;" />

Caption example: "Discharge within 4 hours declined in both cohorts, with a larger drop observed in Metro LHDs by Jul–Sep 2025."

Main findings & next questions

  • Which Local Health Districts are driving the biggest changes?
  • Do attendance numbers or patient mix explain some of the results?
  • Could hospital capacity data help explain the weaker measures?

Project outputs

  • Excel workbook with pivot tables, QA notes and charts
  • One-page summary with simple findings and chart notes
  • Notes on assumptions, limitations and data sources