Sr. Healthcare Data Scientist (Medicare/Medicaid)
$97.97k - $132.25kjobgether
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Healthcare Data Scientist (Medicare/Medicaid) based in Australia.
This role offers the opportunity to apply advanced data science and AI to some of the most complex challenges in healthcare program integrity.
You will analyze large-scale Medicare and Medicaid claims data to uncover patterns associated with fraud, waste, and abuse.
The position combines statistical modeling, machine learning, generative AI, and agent-based technologies to create innovative analytical solutions.
You will work with modern tools including LLMs, embeddings, vector databases, and retrieval-augmented pipelines.
Your insights will support better decision-making, operational efficiency, and stronger outcomes across healthcare programs.
The environment is collaborative and mission-driven, with opportunities to translate sophisticated technical work into clear recommendations for diverse audiences.
This is an ideal opportunity for a curious, hands-on data scientist who wants to make meaningful impact through healthcare analytics and emerging AI technologies.
Accountabilities
- Analyze Medicare and Medicaid claims data using statistical methods, machine learning, and advanced analytical techniques to identify trends, anomalies, and potential fraud, waste, and abuse.
- Develop generative AI-powered solutions and agent-based systems to strengthen fraud detection, investigate complex patterns, and improve business processes.
- Build predictive, anomaly detection, and other analytical models that improve program integrity, operational efficiency, and actionable insights.
- Identify opportunities to apply large-scale CMS data with modern AI and machine learning approaches, including LLMs, embeddings, vector databases, and retrieval-augmented generation pipelines.
- Apply sound data science practices including feature engineering, attribute selection, threshold setting, model validation, and train/test methodologies.
- Create clear and effective data visualizations that communicate complex findings and emerging trends.
- Present analytical results and recommendations to both technical and non-technical stakeholders, including senior leadership.
- Contribute to additional analytical, data science, and AI initiatives as required.
Requirements
- Bachelor’s degree in an analytical or technical discipline such as Statistics, Computer Engineering, Applied Mathematics, Data Science, or a related field, or equivalent relevant experience.
- At least 5 years of professional experience in data science, including experience developing and applying advanced analytical models.
- At least 2 years of hands-on experience analyzing Medicare and/or Medicaid data, with a strong understanding of healthcare claims and program data.
- Proficiency in Python or R for data science and machine learning, with experience using tools such as Pandas, NumPy, TensorFlow, Scikit-learn, Seaborn, ggplot, or Matplotlib.
- Working knowledge of SQL and modern data platforms and technologies such as Databricks, Snowflake, and Spark.
- Hands-on experience with generative AI technologies and frameworks, such as LangChain, LangGraph, Hugging Face Transformers, vector databases, agent frameworks, or LLM orchestration tools.
- Strong understanding of statistics, machine learning fundamentals, predictive modeling, feature engineering, and model evaluation principles.
- Ability to lead analytical work independently while collaborating effectively across technical and business teams.
- Strong visualization, communication, and storytelling skills, with the ability to simplify complex data and AI concepts for varied audiences.
- A proactive, curious, self-directed mindset combined with strong problem-solving skills and a practical approach to applying emerging technologies.
Benefits
- Estimated annual salary range of $97,968–$132,250 , with actual compensation determined by experience, geographic location, and applicable contractual requirements.
- Fully remote work environment with a standard 40-hour work week .
- Limited travel, generally less than 10% .
- Multiple medical plan options, including plans with Health Savings Accounts.
- Dental and vision insurance options.
- 401(k) retirement savings plan with company matching and pre- and post-tax contribution options.
- Flexible work arrangements where applicable to support work-life balance.
- Paid vacation, sick, personal, and holiday time, with typically 15 days of paid leave plus 10 paid holidays for new employees, subject to applicable policies and proration.
- Paid parental, military, bereavement, and jury-duty leave.
- Up to 160 hours of paid family leave during a rolling 12-month period for eligible employees.
- Short- and long-term disability coverage, life insurance, accidental death and dismemberment coverage, and additional accident and critical illness benefits.
- Opportunities to work with modern AI, cloud, data, and analytics technologies on impactful healthcare initiatives.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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