Data Scientist

Solace

. Develop and refine machine learning models for patient churn prediction, operational volume estimation, and advocate quality scoring .

Posted 10/5/2026full-timeRemote • United StatesMid-LevelSenior💰 $160,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing machine learning models and applying advanced statistical methods to derive insights from complex datasets. Proficient in translating technical findings into actionable narratives for diverse stakeholders while ensuring compliance with privacy standards.

Highest-signal resume keywords

Machine Learning Model DevelopmentStatistical Analysis and Hypothesis TestingPython Data Science EcosystemTime-Series Forecasting TechniquesSQL Query Writing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

StatisticsProbabilityRegression AnalysisTime-Series ForecastingARIMAProphetExponential SmoothingData AnalysisComplex SQL QueriesStatistical Methods

Soft Skills

Self-StarterOwnershipAdaptabilityCommunicationProblem-Solving

Tools & Technologies

PythonPandasScikit-LearnStatsmodelsNumPySnowflakeDockerAirflowMLflowDbt

Certifications & Qualifications

Master's Degree in Data SciencePhD in Applied Science

Industry Keywords

Healthcare DataInsurance Claims DataPHIPIINLP TechniquesCausal InferenceA/B TestingCapacity PlanningResource AllocationMatching Algorithms

Tech Stack

Tools & technologies

AirflowDockerNumpyPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Develop and refine machine learning models for patient churn prediction, operational volume estimation, and advocate quality scoring
Own time-series forecasts for capacity planning and resource allocation
Lead the design and analysis of A/B tests and causal inference studies
Apply advanced statistical methods to complex datasets to uncover patterns and answer difficult business questions
Work with Data Engineers to productionize models within the data infrastructure
Translate complex statistical findings into clear, actionable narratives for non-technical stakeholders
Report directly to the VP of Data
Lead high-impact projects influencing strategic decision-making

Requirements

What you’ll need

Strong background in statistics, probability, and mathematics, including hypothesis testing, regression analysis, and time-series forecasting
Fluency in Python and its data science ecosystem: pandas, scikit-learn, statsmodels, and NumPy
Hands-on experience with time-series analysis and forecasting techniques, such as ARIMA, Prophet, and exponential smoothing
Ability to write complex SQL queries and retrieve data from Snowflake
Familiarity with best practices for handling PHI and PII and ensuring privacy in analysis
Self-starter comfortable with ambiguity, ownership, and wearing many hats
Applicants must be based in the United States
Preferred master's degree or PhD in Data Science, Applied Science, or a related field (optional)
Bonus: experience with Docker, Airflow, or MLflow
Bonus: healthcare or insurance claims data experience
Bonus: NLP techniques for unstructured text
Bonus: matching algorithms or ranking systems for two-sided marketplaces
Bonus: reading or writing dbt models

Benefits

Comp & perks

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