Kalderos is building unifying technologies that bring transparency, trust, and equity to the entire healthcare community with a focus on pharmaceutical pricing. The company is looking for a Data Analyst to lead pharmaceutical discount analysis.
Requirements
- Strong programming skills in SQL and Python and experience with libraries like Pandas and NumPy.
- Clear focus on building data models, dashboards, and visualizations in real-world applications.
- Data Visualization: Ability to present complex findings in a clear and effective manner using tools like Tableau to make data accessible to non-technical stakeholders.
- Familiarity with machine learning models.
- Experience building data models, dashboards, ELT pipelines and other services for the healthcare industry
- Experience in medical imaging, genomics, or health analytics is a plus.
Responsibilities
- Collect, transform, and analyze data from electronic health records, patient interactions, and internal systems to support product teams and business strategy.
- Develop reports and dashboards in tools like Tableau or Power BI to provide actionable insights to clinical, product, and executive stakeholders.
- Perform statistical analysis (trend analysis, cohort evaluation, hypothesis testing) to identify patterns and inform data-driven decision-making.
- Ensure data accuracy and integrity through validation, profiling, and collaboration with cross-functional partners (e.g., engineers, clinical operations).
- Support ad-hoc analysis requests and contribute to insights that drive product enhancements, process improvements, and business case development.
Other
- 1-3 years of hands-on experience as a Data Analyst or Data Scientist.
- Problem Solving & Business Orientation: A practical, ROI-driven mindset with the ability to apply data science techniques to generate tangible business value, improving operational efficiency, patient outcomes, or profitability.
- Collaboration & Teamwork: Strong interpersonal skills to work in a team-oriented environment and communicate effectively with both technical and non-technical stakeholders.
- Detail-oriented mindset with a passion for data quality, storytelling, and solving real-world problems
- Excellent communication skills—able to present technical insights clearly to non-technical stakeholders
