Associate Data Scientist (College Grad 2027)

Solace • Redwood City, CA

42d • Hybrid

About The Position

This is a rare chance to learn data science from the inside out at one of the fastest-growing healthcare startups in the country. As an Associate Data Scientist at Solace, you'll work on the forecasting and machine learning systems that operate our marketplace in real time: matching patients with advocates, predicting demand, and keeping the business ahead of its own growth. You won't spend your first year re-deriving textbook exercises. You'll contribute to real models with mentorship from senior data scientists, and you'll be expected to think independently, question your own results, and defend your methodology. You don't need years of experience, but you do need an innate ability to get things done. This role is for the ambitious, the curious, and those who don't shy away from feedback. If you're the kind of person who sees a problem and can't resist solving it, keep reading. This is an in person role in our Redwood City office, 3 days a week.

Requirements

• A bachelor's or master's degree in Statistics, Data Science, Computer Science, Applied Math, or a related quantitative field (or equivalent practical experience), graduating between December 2026 and June 2027.
• Strong fundamentals in statistics and probability: hypothesis testing, regression, and the judgment to know when your model is fooling you.
• Working Python skills, including the core data science ecosystem (pandas, scikit-learn, NumPy), plus working SQL.
• Projects that show you can do real quantitative work: research, internships, Kaggle competitions, hackathons, or personal modeling projects.
• A bias toward action. You have an exceptional craving for momentum, and you'd rather ship a simple model that works than polish a complex one that never launches.
• Curiosity for how systems work, comfort with ambiguity, and a refined palate for controlled chaos.
• Confident communication. You can explain a model to someone who has never heard of one, and take critique of your methodology without defensiveness.
• A sense of care. You take pride in the details, because in healthcare data, the details are the difference.
• A hunger to learn and an ego small enough to admit when you don't know something.

Nice To Haves

• Exposure to time-series forecasting (ARIMA, Prophet, exponential smoothing).
• Coursework or projects in causal inference or experimental design.
• Familiarity with dbt, Airflow, Docker, or cloud environments (AWS).
• Experience with NLP or unstructured text data.

Responsibilities

• Contribute to real predictive models in your first weeks: forecasting, matching, and scoring systems that the business runs on.
• Pull and wrangle your own data with SQL from Snowflake.
• Support the design and analysis of A/B tests and experiments, learning how to measure the true impact of product and operational changes.
• Work alongside data engineers to see how models get from a notebook into production, learning MLOps practices as you go.
• Apply statistics with rigor: knowing when a result is real, when it's noise, and how to tell the difference.
• Present your findings and defend your methodology to technical and non-technical audiences.
• Grow your craft: learn how to frame problems, validate models, design experiments, and make smart modeling decisions.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level