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Inspiren

Senior Data Scientist

Posted An Hour Ago
Easy Apply
In-Office or Remote
Hiring Remotely in United States
170K-200K Annually
Senior level
Easy Apply
In-Office or Remote
Hiring Remotely in United States
170K-200K Annually
Senior level
The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.
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About Inspiren 

Inspiren offers the most complete and connected ecosystem in senior living. Founded by Michael Wang, a former Green Beret turned cardiothoracic nurse, Inspiren proves that compassionate care and technology can coexist - bringing peace of mind to residents, families, and staff.

Our integrated solutions seamlessly fit into existing workflows, capturing everything happening within a community. Backed by nurse specialists and powerful analytics, we provide the data operators need to make informed clinical and operational decisions - driving efficiency, profitability, and better care outcomes.

About the Role

We're looking for a Senior Data Scientist to bring rigor, modeling depth, and a bias toward automation to the data that powers Inspiren. You'll work across the organization, including with our Computer Vision, Machine Learning Engineering, Hardware, and Embedded Systems teams, building models, designing statistical evaluations, and turning one-off analyses into durable workflows that keep improving the product. You should be deeply familiar with the end-to-end ML lifecycle, comfortable reasoning about both classical statistics and modern ML systems, and energized by the opportunity to weave AI into data science workflows.

What you'll do

  • Build models and statistical analyses that surface insights about outcomes and performance across Inspiren’s systems
  • Design and run rigorous evaluations: offline and online experiments (A/B, shadow deploys, etc.) for new models and product changes
  • Identify, evaluate, and integrate new datasets that expand what we can learn and measure
  • Lead root-cause investigations when models or systems underperform in the field, and turn findings into concrete recommendations for improvement
  • Incorporate AI into data science workflows, using LLMs and agentic tooling to accelerate analysis, code generation, documentation, and decision-making, and help shape how the team adopts these practices
  • Reason how to incorporate multiple modalities and sensor data into algorithmic development and performance measurement

About you

  • 5+ years of experience in data science, with a focus on statistical modeling and ML systems
  • Strong modeling and statistical foundations. You're comfortable choosing the right tool for the problem, whether simple heuristics through ML
  • Experience partnering with ML engineering teams, including familiarity with how production ML systems are evaluated and monitored
  • Fluency with a modern data science stack: Python, Pandas, PyTorch, Databricks, MLflow, or similar tools for working with data and ML at scale
  • Hands-on experience using AI tools (LLMs, coding copilots, agentic workflows) to speed up your own work, and curiosity to experiment with AI tools
  • Strong data instincts and a pragmatic bias toward solutions that work in messy, real-world conditions
  • A collaborative mindset and interest in working with a diverse teams
  • Able to scope, prioritize, and deliver work independently
  • Excited about working at an early-stage startup where your work directly shapes care outcomes

Bonus skills

  • Experience working on spatiotemporal problems (sensor data, trajectories, event streams, or similar)
  • Experience working with health or clinical data
  • Healthcare or senior living domain experience

Details

  • The annual salary for this role is $170,000-$200,000 + equity + benefits (including medical, dental, and vision) 
  • Flexible PTO
  • Location: Remote, US or Canada. NYC preferred.
  • Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.

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