Data Scientist

About the Role

The Solace Data Team is seeking a Data Scientist to develop and refine machine learning models that predict patient churn, estimate operational volume, and score advocate quality. This role involves building predictive models, driving forecasting rigor, designing and analyzing experiments, uncovering deep insights, and producing solutions ready for production.

What You'll Do

• Build Predictive Models: Develop and refine machine learning models to solve critical business problems, such as predicting patient churn, estimating operational volume, or scoring advocate quality.
• Drive Forecasting Rigor: Own the development of time-series forecasts that guide our capacity planning and resource allocation. Help us anticipate "what comes next" with higher accuracy.
• Design & Analyze Experiments: Lead the design and analysis of A/B tests and causal inference studies. Ensure we measure the true impact of our product and operational changes.
• Uncover Deep Insights: Apply advanced statistical methods to complex datasets to find patterns that simple reporting might miss. Answer the "why" and "how" behind our most difficult questions.
• Productionize Solutions: Work closely with Data Engineers to take your models from a local notebook to a production environment, ensuring they run reliably within our data infrastructure.
• Communicate Complexity: Translate complex statistical findings into clear, actionable narratives for non-technical stakeholders. Be the voice of statistical reason in strategic discussions.

What You Bring

• Statistical Expertise: Strong background in statistics, probability, and mathematics (e.g., hypothesis testing, regression analysis, time-series forecasting).
• Python & ML Proficiency: Fluent in Python and its data science ecosystem (pandas, scikit-learn, statsmodels, NumPy). Writes clean, reproducible code.
• Forecasting Experience: Hands-on experience with time-series analysis and forecasting techniques (e.g., ARIMA, Prophet, exponential smoothing).
• Advanced SQL: Can write complex queries to wrangle your own data from Snowflake without relying solely on others to prepare it for you.
• PREFERRED: Masters Degree or PHD in Data Science, Applied Science, or related fields.
• Data Privacy Awareness: Understands the importance of protecting patient data. Familiar with best practices for handling PHI and PII and ensuring privacy in your analysis.
• Startup DNA: Self-starter who is comfortable with ambiguity. Takes ownership of problems and is willing to wear many hats to get the job done.

Bonus Points

• Deployment Experience: Experience using tools like Docker, Airflow, or MLflow to deploy and monitor models in production.
• Healthcare Experience: Experience working with healthcare or insurance claims data is a plus.
• NLP & Unstructured Data: Experience applying Natural Language Processing (NLP) techniques to extract insights from unstructured text data.
• Marketplace Matching: Experience designing matching algorithms or ranking systems for two-sided marketplaces.
• dbt & Engineering Skills: Comfort reading or writing dbt models to understand the lineage of your data.