ABOUT AWARE HEALTH

Everyday, 50% or more of the workforce show up to work with pain, joint stiffness, muscle strain, or other physical impairments due to musculoskeletal (MSK) and orthopedic conditions. Too often, these conditions are misdiagnosed and treated passively with opioids, injections or costly surgeries. These expensive and risky treatment methods can often be avoided altogether with more modern approaches to preventing, diagnosing and treating MSK pain.
At Aware Health, our mission is to empower individuals to reach their goals through compassionate care, accurate diagnostics and precision treatment. We are a team of learners and collaborators driven by results and integrity. Our platform ensures patients get the right care—avoiding inappropriate and frequently unnecessary tests, drugs, and surgeries.
We are on track for 200%+ growth this year, and looking for ambitious candidates who are excited to embrace the challenges of a startup environment while improving the health of millions of people.

ABOUT THE JOB

We are looking for a highly motivated data analyst with experience working in a fast-paced startup environment and a track record of analyzing large, complex datasets to generate key business insights and drive outcomes. Flexibility, proactivity, and a healthy sense of urgency are vital to this role. You will need expertise in data analysis and proficiency with tools like SQL, Python/notebooks, dashboards and business intelligence tools — as well as solid experience working with source data from modern data warehouses and ETL pipelines. Our current data stack includes AWS/Athena/etc, Postgres, Python, MLFlow, Airbyte, LlamaIndex, LangChain, BI Tools, data lakes/warehouses/S3, and AI/ML models.
The reports and insights you generate will inform decisions across the company—from the CEO to sales, customer success, and clinical teams—and will also play a critical role in training and developing AI/ML models.
Our culture is ambitious yet humble, and we care greatly about the impact we make. We value in-person collaboration, requiring three days per week in our San Francisco office. While we prioritize well-being, we are not a 9-to-5 culture, and at times critical deadlines may require extra effort. We balance high-impact work with time to recharge.
We are looking for smart, driven people. Please consider applying if you believe you are a strong candidate, even if you don’t check off all our requirements below.

REQUIRED QUALIFICATIONS:

• Energized to work in ambiguous, fast-paced startup cultures and isn’t discouraged by being in an environment where we don’t have it all figured out yet
• An open, curious, and humble mindset that drives experimentation, creativity, and trying new things — while operating with a sense of urgency
• 2+ years of experience working with large data sets as a data analyst, data scientist, or similar role
• Expertise with SQL and Python; familiarity with common data stacks (numpy, pandas, matplotlib, scikit-learn, Jupyter notebooks, etc)
• Experience applying a wide range of statistical techniques to large data sets, and understanding their real-world advantages/drawbacks
• Strong organizational skills, with ability to manage multiple projects in parallel, juggle frequent incoming requests, and consistently deliver results on time
• Strong communication skills, with ability to present findings to non-technical audiences
• A desire to grow further in artificial intelligence, machine learning, and/or data science

BONUS QUALIFICATIONS:

• Strong preference for candidates with a background in digital health, including experience with PHI/PII, claims data analysis, clinical coding systems (e.g. ICD-10, CPT), health data modeling, and clinical risk prediction
• Degree in business analytics, statistics, data science, computer science, machine learning, or a related field is highly desired
• Experience with PyTorch, TensorFlow, and machine learning algorithms like random forest, linear and logistic regressions, gradient boosting, classification, GANs, and anomaly detection algorithms for building, evaluating, deploying and monitoring ML models from scratch
• Experience with data engineering, building data processing pipelines, and/or deploying and training AI/ML models

• Direct support for the frequent, ad hoc data needs of our CEO and sales/clinical/customer teams, often requiring rapid iterations and quick turnaround to support business/customer urgency
• Data analysis, trends/pattern identification, prospective analysis and forecasting, calculating ROI and other KPIs
• Data reporting including data visualization, building dashboards, drive insights and articulating conclusions
• Writing SQL and Python code, maintaining Jupyter notebooks, and working with related technologies
• Assists with data collection strategies, often requiring frequent follow-ups and managing multiple customers in parallel
• Keep up with the newest developments in data analysis and/or business intelligence