Applied Data Scientist

About Vi Muuv Labs merged with Vi Labs and is now a Vi Company. Muuv Labs helps health and wellness companies develop the next generation of products, faster and more affordably than ever before. WHAT IS MUUV LABS: * Muuv Labs is a full innovation lab that is leveraging user research and deep data analysis to predict and build future innovations in the health and wellness industry * Muuv Labs is a world class mix of behavioral psychologists, kinesiologists, content creators and technologists with a passion for wellness who help you understand human behavior, design customer centric products, develop, and market them; * Muuv Labs is a consortium of strategic partners who help us do postdoctoral level research, integrate media into your products, manufacture, market, and distribute your products, and generate revenue from your list and audience; * Muuv Labs is an extensive portfolio of modular and reusable IP to deliver solutions rapidly and in a cost-effective manner. * Muuv Labs is a portfolio of investors who can provide you the capital you need to fund your innovation. WHO WE WORK WITH: * 24 Hour Fitness * Stamina Products/ Walmart Athletic Works * Anytime Fitness * Self Esteem Brands * The Bar Method * Stronger U Nutrition WHAT WE DELIVER: Our work is proven to lead to a higher roi than internal efforts * New Product Innovation: We discover and create the latest in fitness technology, both for our clients and internally. * Digital Transformation: We have proven methods to shift existing businesses into a digital focused model. * Digital Enablement: We are able to solve specific, targeted problems that clients may have within their existing digital ecosystem. * Digital Services: We can provide full stack services for smaller, independent businesses.

Vi

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V

muuvlabs.com

11-50 employees

Wellness and Fitness Services

Austin, Texas

Privately Held

592 LinkedIn followers

• Vi Engage puts predictive models into the daily operations of the largest health systems and health plans in the country — driving care navigation, specialty capture, and the workflows that follow from them. Applied Data Scientists are the people who turn a new customer into a running deployment on Vi's platform.
• You will own 3–5 enterprise healthcare accounts at a time, end to end. For each one you are the data expert in the room: you design the pilot that proves value, integrate the customer's data (tokens, claims, EHR, marketing) into Vi's platform and build the automated pipelines that train, score, and deliver insights on a schedule. You stay the technical owner through operations and drive accounts to “autopilot”.
• This is a hands-on-keyboard role with direct exposure to stakeholders. You are expected to sit with customer teams with expertise in analytics, marketing, and clinical operations to understand what KPIs they need to move, and how to leverage Vi’s capabilities to make it a reality. What you learn in the field becomes the product: you will spot the patterns across your accounts and turn them into the requirements that shape Vi's roadmap.
• Data integration. Own the pipeline between customer data systems and Vi's data platform — ingestion, mapping, quality, and the judgment calls about what the data can and cannot support.
• Pilot design. Design studies that tie model performance to a business outcome the customer will underwrite. Power, controls, confounders, and a metric that survives scrutiny from a sophisticated internal analytics team.
• Automated production pipelines. Build per-customer pipelines that use Vi’s ML capabilities to train, score, and deliver insights without manual intervention — and keep them running.
• Customer ownership. Be the technical authority across onboarding and ongoing operations, including the ad-hoc data and reporting questions that come with a live account.
• Product leverage. Identify what's common across customers and synthesize it into high-leverage requirements for the platform, so the next deployment is faster than the last.
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Required

• Experimental design you can defend. You have designed and run studies where the result mattered commercially — and you can explain, to a skeptical stakeholder, why the design supports the conclusion. This is the capability we screen hardest on.
• Real data science depth. You can explain how a model works, evaluate it honestly, and say what it is not good for. You know when a simpler approach is the right answer.
• Python and ML engineering. Fluent in Python and the working stack — pandas, sklearn, airflow. You ship code to production that automates client deliverables.
• PySpark at scale. You have built distributed data and ML pipelines on Spark against large, messy datasets.
• Client-facing command. You can run a working session with clinical, IT, and analytics leaders at a major health system or health plan on your own — translating between their business problem and what the data will actually support, and holding the line when the answer isn't what they hoped. You will occasionally travel onsite with clients.
• Ownership instinct. You treat your accounts as yours: you find the problem before the customer does and you fix it.
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Preferred

• Healthcare or life sciences domain knowledge — claims, EHR, HL7/FHIR, lab data, or population health analytics
• Experience designing and optimizing the targeting of marketing and engagement campaigns
• AWS data infrastructure: S3, Glue, EMR, MWAA, SageMaker
• Familiarity with HIPAA and healthcare compliance and data governance frameworks
• Experience taking a product from its first customer deployment to a repeatable one
• This is an applied, in-production role. It is not a research position — the work is measured by deployments that run and outcomes customers can point to, not by novelty. And it is not a delivery or engagement management role: you will be architecting and writing the pipelines yourself, not coordinating someone else who does.
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• Why choose Vi?
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• Why choose Muuv?
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