Sr Applied Scientist (Python, NumPy & AWS - HealthTech)
- Seattle, WA, USA
Accolade is a personalized health and benefits solution that dramatically improves the experience, outcomes and cost of healthcare for employers, health plans and their members. With a unique blend of compassionate advisors, clinical experts and intelligent technologies, we engage individuals and families in their health, establish trust, and influence their decisions at every stage of care. Accolade connects the widest array of personal health data and programs to present a single point of contact to the most effective health and benefits resources, while coordinating with providers at every step. Accolade consistently achieves 70 and higher Net Promoter Scores, 98% consumer satisfaction ratings, and up to 15% employer cost savings. Accolade has been recognized as one of the nation’s 25 most promising companies by Forbes, a fastest-growing private healthcare company by Inc. 5000, and is consistently rated a Top Workplace across the country. For more information, visit accolade.com.
The Senior Applied Scientist, reporting to the Senior Director of Data Science, is responsible for modeling large health and engagement data sets. In this role you will propose, create, and deploy models on a multi-channel cloud platform, improving client well-being through better utilization of health care and benefits.
A day in the life…
- Apply statistical expertise to large data sets with billions of data points, representing hundreds of millions of lives, for the purpose of improving health outcomes
- Deploy personalized models to millions of Accolade clients, providing guidance for health decisions and improving lives and well-being
- Apply engagement models across a variety of channels, including client-initiated channels like mobile, messaging, and web, and outreach channels such as email and text
- Review the latest scientific literature to identify modeling proposals, creating prototypes on large population health datasets
- Serve as a domain expert for statistical techniques as applied to machine learning on population health
- Serve as a domain expert for statistical techniques applied to operational data such as anomaly detection, forecasting, and AB testing
- Augment "black box" population health models with interpretability, surfacing relevant information for a human in the loop
- Collaborate across Accolade with a multidisciplinary group of researchers and industry experts, including specialists in machine learning, behavioral science, big data, epidemiology, and population health
What we are looking for…
- PhD in Statistics or a closely related area
- Solid understanding of probability and combinatorics, sampling theory, and concepts related to statistical hypothesis testing
- Solid understanding of Bayesian methods for inference, modeling, and experimentation
- Working familiarity with machine learning techniques, metrics, and processes
- Experience coding in Python including scientific libraries such as NumPy, Scipy-stats and scikit-learn
- Ability to source and transform data using SQL and pandas
- Experience or interest working in a cloud environment, such as AWS or GCP
- Familiarity with clinical and billing data such as ICD and CPT codes, 835/837, or actuarial data preferred
What is important to us
Creating an enduring company that is hyper-focused on our culture and making a meaningful impact in the lives of our employees, members and customers. The secret to our success is:
We find joy and purpose in serving others
Making a difference in our members’ and customers’ lives is what we do. Even when it’s hard, we do the right thing for the right reasons.
We are strong individually and together, we’re powerful
Trusting in our colleagues and embracing their different backgrounds and experiences enable us to solve tough problems in creative ways, having fun along the way.
We roll up our sleeves and get stuff done
Results motivate us. And we aren't afraid of the hard work or tough decisions needed to get us there.
We’re boldly and relentlessly reinventing healthcare
We're curious and act big -- not afraid to knock down barriers or take calculated risks to change the world, one person at a time.
All your information will be kept confidential according to EEO guidelines.