[All remote jobs](https://jobicy.com/jobs.md)[![Solace logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/4e37a66b-221.png)](https://jobicy.com/company/solace.md)[Solace](https://jobicy.com/company/solace.md) # Data Scientist AI Summary Solace is seeking a Data Scientist to develop predictive models, forecasting systems, and experimental analyses for a rapidly growing healthcare-advocacy platform. The role owns high-impact work such as patient-risk and churn modeling, operational-volume forecasting, A/B testing, and causal inference. The successful candidate will use Python, SQL, statistical methods, and machine-learning workflows while partnering with data engineers to productionize reliable models. This is a fast-paced, high-autonomy startup role reporting to the VP of Data, with a strong emphasis on communicating actionable findings to non-technical leaders.[Apply for this job](#job-application)[View company](https://jobicy.com/company/solace.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 160k–200k / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceDirectorPublished6 Nov 2026Apply before6 Dec 2026Listing views43Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. ### About Solace Healthcare in the U.S. is fundamentally broken. The system is so complex that 88% of U.S. adults do not have the health literacy necessary to navigate it without help. Solace cuts through the red tape of healthcare by pairing patients with expert advocates and giving them the tools to make better decisions—and get better outcomes. We’re a Series C startup, founded in 2022 and backed by Inspired Capital, Craft Ventures, Torch Capital, Menlo Ventures, Signalfire, and IVP. Our U.S. based team is lean, mission-driven, and growing quickly. Solace isn’t a place to coast. We’re here to redefine healthcare—and that demands urgency, precision, and heart. If you’re looking to stretch yourself, sharpen your edge, and do the best work of your life alongside a team that cares deeply, you’re in the right place. We’re intense, and we like it that way. Read more in our Bloomberg funding announcement [here](https://www.bloomberg.com/news/articles/2026-02-10/vcs-give-solace-health-1-billion-valuation-for-patient-advocacy-tech?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc3MDczMDg4MywiZXhwIjoxNzcxMzM1NjgzLCJhcnRpY2xlSWQiOiJUQThVUzhLR0NURzEwMCIsImJjb25uZWN0SWQiOiJBRDYxODI0MTc0ODM0MTk0QTRENUZFNzkwMzNGMDJGNSJ9.TE2pFUAOQAPMUXFlzoQ7zeJvctq7cSibbZqtIwhW-2U&leadSource=uverify+wall). ### About the Role At Solace, data isn’t just about understanding the past; it’s about predicting the future. We are a rapidly scaling startup where we work hard, move fast, and wear many hats. The Solace Data Team is looking for a Data Scientist who excels at forecasting, prediction, and machine learning to help us anticipate patient needs and optimize our operations. Reporting directly to the VP of Data, you will have the opportunity to lead high-impact projects that directly influence our strategic decision-making. In this role, you will go beyond descriptive analytics to build the predictive engines that drive our business. Whether you are forecasting operational volume, modeling patient risk, or designing rigorous A/B tests, you will bridge the gap between advanced statistics and practical business application, ensuring our models are robust, interpretable, and impactful. ### 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. You will 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. You will 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. You will 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. You will be the voice of statistical reason in strategic discussions. ### What You Bring * Statistical Expertise: You have a strong background in statistics, probability, and mathematics (e.g., hypothesis testing, regression analysis, time-series forecasting). * Python & ML Proficiency: You are fluent in Python and its data science ecosystem (pandas, scikit-learn, statsmodels, NumPy). You write clean, reproducible code. * Forecasting Experience: You have hands-on experience with time-series analysis and forecasting techniques (e.g., ARIMA, Prophet, exponential smoothing). * Advanced SQL: You 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: Data Science, Applied Science, or related fields. * Data Privacy Awareness: You understand the importance of protecting patient data. You are familiar with best practices for handling PHI and PII and ensuring privacy in your analysis. * Startup DNA: You are a self-starter who is comfortable with ambiguity. You take ownership of problems and are 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. Applicants must be based in the United States. Up for the Challenge? We look forward to meeting you. Fraudulent Recruitment Advisory: Solace Health will NEVER request bank details or offer employment without an interview. All legitimate communications come from official solace.health emails only or [ashbyhq.com](http://ashbyhq.com). Report suspicious activity to recruiting@solace.health or advocate@solace.health. Show more [Apply now >](https://jobicy.com/jobs/159265-data-scientist-7.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThe position requires advanced statistical judgment across forecasting, experimentation, causal inference, and production machine learning. It also demands independent ownership in an intense startup environment handling sensitive healthcare data. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Highly competitive$180,000US market range (per year)$150k–$210k0$231.00k AI insightThe employer discloses a base salary range of $160,000-$200,000 USD per year, with a midpoint of $180,000. This is a credible annual range for an experienced U.S.-based Data Scientist working on predictive modeling and healthcare data. Estimated U.S. market pay for comparable roles is approximately $150,000-$210,000 per year; this is an AI estimate, not verified salary research. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Time Series Forecasting](https://jobicy.com/jobs?search_keywords=Time%20Series%20Forecasting.md)[Statistical Modeling](https://jobicy.com/jobs?search_keywords=Statistical%20Modeling.md)[A/B Testing](https://jobicy.com/jobs?search_keywords=AB%20Testing.md)[Causal Inference](https://jobicy.com/jobs?search_keywords=Causal%20Inference.md)[pandas](https://jobicy.com/jobs?search_keywords=pandas.md)[scikit-learn](https://jobicy.com/jobs?search_keywords=scikit-learn.md)[Snowflake](https://jobicy.com/jobs?search_keywords=Snowflake.md)[Predictive Analytics](https://jobicy.com/jobs?search_keywords=Predictive%20Analytics.md)[Data Privacy](https://jobicy.com/jobs?search_keywords=Data%20Privacy.md)[Docker](https://jobicy.com/jobs?search_keywords=Docker.md)[Airflow](https://jobicy.com/jobs?search_keywords=Airflow.md)[MLflow](https://jobicy.com/jobs?search_keywords=MLflow.md) Sample interview questionsHow would you build and evaluate a forecast for weekly patient volume?I would first define the forecast horizon and operational decision it supports, then assess data quality, seasonality, holidays, trend changes, and relevant external drivers. I would compare appropriate baselines with models such as exponential smoothing, ARIMA, or Prophet using rolling-origin validation and metrics such as MAE or WAPE. I would present prediction intervals and establish monitoring for error drift after deployment. Describe how you would design an A/B test for a patient-facing workflow change. I would define the primary outcome, guardrail metrics, target population, randomization unit, expected effect size, and required sample size before launch. I would check for assignment integrity and pre-specified stopping rules, then analyze treatment effects with confidence intervals and relevant covariate adjustments. I would also assess heterogeneous effects and clearly communicate both practical and statistical significance. How do you make a machine-learning model useful to non-technical stakeholders? I start with the operational decision and explain the model in terms of outcomes, tradeoffs, and recommended actions rather than algorithm details. I use interpretable features where possible, quantify uncertainty, and provide examples of when predictions should or should not be used. I also create simple dashboards or decision artifacts and collect stakeholder feedback to ensure adoption. What practices would you use to protect PHI and PII in a data-science workflow? I would apply least-privilege access controls, use approved secure environments, minimize data fields, and avoid exposing identifiers in notebooks, logs, or model outputs. I would follow established retention and encryption policies, use de-identified or aggregated data whenever suitable, and review outputs for privacy risks before sharing. I would partner with security and compliance teams when defining data access and deployment controls. How would you take a model from a notebook into production? I would make the training and inference code reproducible, version data and model artifacts, and package the workflow with appropriate tooling such as Docker and MLflow. I would work with data engineering to define reliable inputs, orchestration, testing, and deployment processes. After launch, I would monitor data quality, prediction distributions, model performance, latency, and business outcomes, with a retraining and rollback plan. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. Keep exploring ## Related remote jobs. * ![Doximity logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/e71c16d6-221.jpg) Doximity Nov 6 New ### [Commercial Data Scientist](https://jobicy.com/jobs/154739-commercial-data-scientist.md) Commercial Data Scientist Doximity is the leading clinical AI company with the largest network of U.S. clinicians. 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