Mindoula Health is hiring an early-career Healthcare Data Scientist to play a critical role in building our analytics capabilities. You will provide data-driven insights from a wide range of healthcare data, support program performance measurement, and ensure analytic outputs are reliable.
What You'll Do
- Process and analyze structured and unstructured healthcare data, including claims, assessments, surveys, chat/call logs, and third-party sources.
- Maintain and improve data pipelines and modeling code for scalability, automation, and reproducibility.
- Investigate data issues and contribute to improvements in data quality and integrity.
- Collaborate with team members to conduct analyses and modeling workflows with guidance from senior staff.
- Execute and validate outputs from production notebooks and pipelines, flagging inconsistencies and escalating unusual findings.
- Apply statistical methods—including propensity score matching, difference-in-differences, and time series modeling—to evaluate program impact and calculate ROI.
- Perform ad-hoc and root cause analyses to uncover trends and support findings from evaluations.
- Partner with the data science team to define scopes, participate in code reviews, and support ad-hoc analysis requests.
- Work cross-functionally with data engineering, analytics, and software teams on shared initiatives.
- Help maintain and update technical documentation and training materials.
- Prepare clear and accurate reports for internal use and client deliverables.
- Translate complex analytical findings into accessible insights for business and clinical stakeholders.
What We're Looking For
- A Master’s degree in a quantitative field such as epidemiology, psychology, health administration, public health, computer science, statistics, data science, economics, mathematics, or engineering. A bachelor’s degree with 4+ additional years of equivalent experience will also be considered.
- 2-6 years of experience (internship, specific coursework, and projects apply).
- Experience with health-related data is required (e.g., claims, program data, EHR).
- Statistics coursework and/or training is required; familiarity with core statistical concepts including variance, relative risk, incidence/prevalence.
- Strong foundation in programming languages including SQL, Python, and R.
- Familiarity with programming notebooks (e.g., Jupyter, Databricks) and tools like Pandas or NumPy.
- Experience writing SQL to query relational databases (e.g., Athena, PostgreSQL, MS Access).
- Proven ability to troubleshoot code, technical issues, and uncover root cause data issues.
- Strong attention to detail—able to spot inconsistencies or incorrect values in output.
- Excellent communication and interpersonal skills, with the ability to explain complex concepts to non-technical stakeholders.
- Enthusiasm for working in a collaborative, cross-functional team environment, paired with a proactive, problem-solving mindset.
- Comfort with working in a virtual, remote environment and leveraging virtual communication platforms.
Nice to Have
- Familiarity with causal inference methods (e.g., difference-in-differences, propensity matching).
Technical Stack
- Languages: SQL, Python, R
- Notebooks & Tools: Jupyter, Databricks, Pandas, NumPy
- Databases: Athena, PostgreSQL, MS Access
Team & Environment
You'll join a small but growing team within a collaborative, cross-functional environment.
Work Mode
This role is remote within the United States.
Mindoula Health is an equal opportunity employer.
