Data Scientist

This range is provided by Skale. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$180,000.00 / yr - $220,000.00 / yr

Principal Recruiter – Building ML and engineering teams in the US

We’re working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics.

We’re seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability.

This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions.

Key Responsibilities

Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records)

Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers

Research and prototype innovative approaches leveraging both classical and modern machine learning techniques

Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments

Collaborate cross‑functionally with data engineers, clinicians, and product teams to ensure models address real‑world healthcare needs

Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations

Required Qualifications

Strong foundation in statistical modeling, machine learning, or data science, with preference for experience in temporal or longitudinal data analysis

Proficiency in Python and ML frameworks (PyTorch, JAX, NumPyro, PyMC, etc.)

Proven track record of transitioning models from research prototypes to production systems

Experience with probabilistic methods, survival analysis, or Bayesian inference (highly valued)

Bonus Qualifications

Experience working with clinical data and healthcare terminologies (ICD, CPT, SNOMED CT, LOINC)

Background in actuarial modeling, claims forecasting, or risk adjustment methodologies

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Information Technology

Industries

Staffing and Recruiting

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