Clinical Data Specialist

Function Health

$95K — $115K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years in biostatistics, applied statistics, or epidemiology.
  • Solid foundation in statistical inference and model validation.
  • Proficient in Python and statistical libraries (e.g., NumPy, pandas).
  • Experience designing statistical analysis plans for complex datasets.
  • Familiar with longitudinal data, including missingness and time-dependent effects.
  • Strong skills in interpreting results and communicating uncertainties.
  • Effective collaboration with machine learning and clinical teams.

Responsibilities

  • Design and own statistical analysis plans for validating ML models.
  • Develop rigorous statistical evaluations including performance and calibration.
  • Lead analyses on model behavior across diverse demographics and clinical traits.
  • Partner with ML scientists to determine validation strategies for models.
  • Apply modern statistical methods to contextualize model outputs.
  • Analyze longitudinal health data to track progression over time.
  • Conduct literature reviews to align analyses with best clinical practices.
  • Document analytical assumptions and results for regulatory readiness.
  • Communicate findings and statistical rationale clearly across teams.

Benefits

  • Competitive salary and benefits package.
  • Flexible working hours.
  • Dynamic and innovative work environment.
Full Job Description


Your Mission

As a Clinical Data Specialist, you will be responsible for the statistical design, validation, and analytical rigor underpinning Function Health's machine learning models and clinical insights.

You will work closely with the Engineering, Data, and Clinical teams to ensure that models are evaluated with appropriate statistical methods, validated across relevant populations, and supported by transparent, defensible analysis suitable for healthcare and regulated environments. Your work will focus on defining statistical analysis plans, assessing model performance and reliability, and translating complex results into clinically meaningful evidence.

What you'll do

As a Clinical Data Specialist, you will:

  • Design and own statistical analysis plans (SAPs) to validate machine learning models, including definitions of cohorts, endpoints, metrics, and subgroup analyses.
  • Develop and execute rigorous statistical evaluations of ML models, including performance assessment, calibration analysis, uncertainty quantification, and sensitivity analyses.
  • Lead subgroup, bias, and fairness analyses to understand model behavior across demographics, clinical characteristics, and longitudinal trajectories.
  • Partner with ML scientists to define appropriate validation strategies, including cross-validation, temporal validation, external validation, and robustness testing.
  • Apply classical and modern statistical methods (e.g., regression, survival analysis, mixed-effects models) to contextualize and validate model outputs.
  • Analyze longitudinal health data to assess change over time, progression patterns, and stability of model predictions in the presence of missingness and real-world noise.
  • Conduct literature review and methodological research to ensure analyses align with clinical standards and best practices in biostatistics and epidemiology.
  • Document analytical assumptions, limitations, and results clearly to support auditability, interpretability, and regulatory readiness.
  • Communicate findings and statistical rationale to clinicians, product leaders, and engineers, translating technical results into clear clinical insights.


Who you are

You care deeply about correctness, rigor, and interpretability, especially when data and models may influence real health decisions. You are comfortable working alongside engineering teams while maintaining an independent statistical perspective focused on validation and evidence.

You enjoy working in cross-functional environments and can clearly explain statistical concepts, uncertainty, and limitations to both technical and non-technical audiences.

Key requirements

  • 3+ years of experience in biostatistics, applied statistics, epidemiology, or a related quantitative role.
  • Strong foundation in statistical inference, experimental design, and model validation.
  • Proficiency in Python and statistical libraries (e.g., NumPy, pandas, SciPy, statsmodels); experience working alongside ML workflows.
  • Experience designing and executing statistical analysis plans for complex datasets.
  • Familiarity with longitudinal and real-world data, including missingness, censoring, and time-dependent effects.
  • Strong skills in interpreting results, assessing uncertainty, and communicating limitations.
  • Ability to collaborate effectively with machine learning, engineering, and clinical teams.


Nice to have

  • Experience validating or supporting machine learning models in healthcare or other regulated domains.
  • Background in survival analysis, causal inference, or longitudinal modeling techniques.
  • Familiarity with model evaluation concepts such as calibration, discrimination, and decision-curve analysis.
  • Exposure to fairness, bias assessment, and subgroup performance analysis.
  • Experience working with PHI-sensitive data and compliance-driven environments.
  • Advanced degree (MS or PhD) in biostatistics, statistics, epidemiology, public health, or a related field.


Why You'll Love Working With Us:

We value our team and offer a competitive salary and benefits package, flexible working hours, and a dynamic work environment where creativity and innovation are encouraged. If you are a highly motivated and experienced individual who is passionate about using technology to improve people's lives, we would love to hear from you.

Join our team and become a part of our mission to revolutionize healthcare. Work with us to make a difference in the lives of thousands, ensuring a healthier future for all. Discover more about us and how we're changing the face of healthcare at Function Health.

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