I'm Mia, a data scientist in healthcare currently leading pricing modelling and negotiations for a $2.2B hospital network. I know exactly what data analytics/data science interviews test — technical cases, behavioural rounds, take-home assignments — and I help you turn your project experience into the answers interviewers actually want to hear.
I currently lead pricing and funding negotiations for a $2.2B health system spanning 17 hospitals, working across DRG case-based pricing, per-diem models, and scenario modelling — negotiating contract terms directly with seven major health funds.
My time at Medibank and EY showed me the other side of the coin — I've walked the road from running the analysis to leading the business decision myself. Now I use that "evidence-first storytelling" method to help job seekers turn their experience into something clear and convincing.
What I offer isn't templated advice — it's built the way I'd build a pricing proposal: find your most compelling "data point" first, then structure it into a narrative an interviewer can't argue with.
This path — from data executor to business decision-maker — is the growth arc I break down most often with clients in career coaching.
Leading pricing negotiations for a $2.2B, 17-hospital health network. Cut HAC (Hospital-Acquired Complication) liability by 50%, secured a 10% annual uplift in HBF contract negotiations, and built DRG and per-diem pricing models to support overall commercial strategy.
Provided data support for hospital contract negotiations, built provider benchmarking models, and improved stakeholder access to performance insights with self-service Tableau dashboards.
Delivered end-to-end analytics and BI solutions across healthcare, government, and energy clients, improved reporting automation, and led the cloud migration from Azure Synapse to Databricks.
This is where most data analyst/data scientist job seekers get stuck: the project happened, but they don't know how to tell it. Here's how I break down my own real work into the answer structures each interview stage needs — the exact method I'll coach you through in mock interviews.
Used SQL to find a funding-model error in raw claims data, quantified the impact, and drove the fix. "Find the problem → quantify the impact → drive the change" is exactly the answer structure a technical case round is listening for.
Turned a repetitive manual report into a self-service dashboard using Power BI/Tableau. "I simplified a process" projects like this are ready-made material for "Tell me about a time..." behavioural questions.
Built what-if scenario models in Python to support business decisions. Many data analyst/scientist take-home assignments are testing exactly this: turn a pile of data into a business conclusion.
Every international student job hunting in Australia runs into this catch-22. I lived through it myself — these three services exist to break that loop.
1-on-1 mock SQL/Python technical interviews, behavioural rounds, and case interviews. Local interviewers don't care how much you've done — they care how you tell it. I'll help you translate overseas/academic experience into language local data teams recognise.
Book a mock interview →Keyword-optimised for data analyst/data scientist roles to get past the ATS. Recruiters scan a resume in about six seconds, and "not enough local experience" is the fastest way for an international student's resume to get cut. I'll help you rebuild the narrative into measurable business results.
Book a resume review →How do you actually go from data analyst to data scientist? Not sure where to start building that first bit of "local experience"? I'll help you map out a realistic path, step by step, out of the catch-22.
Book career coaching →Whether you want to run through a mock interview or completely rewrite your resume, tell me where you're at.