Applied Scientist, Patient Intelligence (Telehealth UX)

Bask Health; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Bask Health is seeking an Applied Scientist, Patient Intelligence to develop ML models and data-driven capabilities that enhance understanding of patient experiences within our telehealth platform. You will work with structured datasets, event data, and approved patient information to build predictive models and intelligent features that guide product decisions.

In this hands-on role, you will collaborate with product managers, data specialists, ML engineers, and software engineers to design

Qualifications

• 3+ years of professional experience in applied machine learning, data science, applied research, or a closely related technical field.
• Strong programming skills in Python or comparable languages used for machine learning and statistical analysis.
• Experience developing and evaluating machine learning models using real-world datasets.
• Strong understanding of supervised learning, classification, regression, and predictive modeling.
• Familiarity with statistical analysis and experimental design.
• Experience using Python data science and machine learning libraries.
• Proficiency with SQL and working with structured datasets.
• Experience cleaning, transforming, and validating data for analysis and modeling.
• Understanding of feature engineering and model training workflows.
• Familiarity with appropriate model evaluation metrics and validation techniques.
• Ability to identify overfitting, data leakage, and other common modeling problems.
• Experience conducting exploratory data analysis.
• Understanding of statistical significance, confidence intervals, and experimental uncertainty.
• Familiarity with A/B testing or controlled experimentation.
• Ability to translate product or business questions into measurable analytical problems.
• Experience communicating technical findings to nontechnical stakeholders.
• Familiarity with reproducible research and version-controlled development.
• Understanding of production machine learning considerations.
• Ability to collaborate with software engineers on model integration.
• Experience evaluating data quality and identifying inconsistent or incomplete records.
• Understanding of responsible data use and privacy-conscious analytical practices.
• Ability to recognize limitations in observational data and model predictions.
• Strong analytical thinking and problem-solving skills.
• Excellent attention to detail and documentation practices.
• Ability to independently own applied research and modeling projects.

Responsibilities

• Develop machine learning models that support patient experience and operational intelligence across Bask Health.
• Analyze patient journey data to identify friction points, behavioral patterns, and opportunities for product improvement.
• Build predictive models for approved patient engagement and workflow outcomes.
• Develop models that help identify potential onboarding abandonment and incomplete workflows.
• Analyze questionnaire completion patterns and other patient interaction signals.
• Create segmentation models that help product teams understand different patient experience patterns.
• Design and implement machine learning approaches for classification, prediction, and behavioral analysis.
• Develop feature engineering pipelines using structured application and event data.
• Build reproducible training, validation, and evaluation workflows.
• Evaluate model performance using appropriate statistical and machine learning metrics.
• Design experiments to assess the effectiveness of intelligent product features.
• Collaborate with product managers to define measurable research questions and success criteria.
• Analyze experiment results and communicate actionable findings.
• Develop methods for identifying changes in patient engagement and workflow behavior.
• Work with engineers to integrate approved machine learning capabilities into production applications.
• Build prototypes that demonstrate the practical value of new modeling approaches.
• Evaluate baseline statistical methods against more complex machine learning models.
• Investigate model errors, data quality problems, and unexpected prediction behavior.
• Monitor model performance and identify potential data or concept drift.
• Develop dashboards, reports, and analytical outputs that communicate model findings.
• Collaborate with engineering teams to improve data collection and event instrumentation.
• Document modeling assumptions, evaluation methodologies, and known limitations.
• Evaluate models for potential bias, inconsistent performance, and unintended consequences.
• Ensure appropriate handling of sensitive patient and operational information.
• Support responsible experimentation and controlled deployment of predictive features.
• Participate in technical discussions, research reviews, and engineering planning.
• Stay current with relevant advances in applied machine learning and statistical modeling.
• Own assigned applied science projects from problem definition through experimentation, evaluation, and implementation support.

Skills

Python

SQL

Machine learning

Statistical analysis

Experiment design

Data analysis

Communication of results

Reproducible research

Tools

scikit-learn

PyTorch

TensorFlow

Job description

Bask Health is seeking an Applied Scientist, Patient Intelligence to develop ML models and data-driven capabilities that enhance understanding of patient experiences within our telehealth platform. You will work with structured datasets, event data, and approved patient information to build predictive models and intelligent features that guide product decisions.

In this hands-on role, you will collaborate with product managers, data specialists, ML engineers, and software engineers to design