Lead Data Scientist

About Stellar Health:

Historically, US Healthcare has relied on a fee-for-service reimbursement system where providers are paid based on the quantity of patient visits and procedures, rather than the quality of health outcomes. 

At Stellar Health, we help primary care providers put patient health first. Our platform - a mix of technology, people, and analytics - supports providers at the point of care, delivering real-time patient information, activating practice staff, and empowering providers and care teams with incentives that reward the work they are already doing to keep patients healthy. Using the Stellar App, our web-based, point-of-care tool; practices receive a simple checklist of recommended actions that support the best quality care. Providers and care teams are then paid monthly for each action they complete, and Payors save money in reduced healthcare costs along the way.  

Stellar is a US-based Health-tech backed by Top VCs (General Atlantic, Point72, & Primary Venture Partners)​​ with an established product & proven operating model. We’ve shown that we make a real difference for physician practices and their patients.

About the position:

Stellar Health is looking for our first product-focused data science hire!  The Lead Data Scientist will report to Stellar’s VP, Engineering, and closely partner with key stakeholders across Engineering, Product & Analytics.

The Lead Data Scientist will collaborate with a product development team focused on measuring, optimizing, automating and scaling Stellar’s innovative incentives strategy to drive quantifiable improvements to healthcare outcomes.

Imagine tackling questions such as, "how can we price payouts to providers to maximize colon cancer screenings for those in need?" Or, "when should we launch competitions across provider groups to deliver higher quality care?" This is an opportunity to take ownership of impactful projects, bringing not just technical expertise but the vision to see them succeed.

Stellar is at an inflection point – we have deep relationships with the key national payors, and a large, fast-growing provider network. We have access to a variety of rich data sources and we’ve invested in upleveling the data infrastructure that will allow us to transform this into insights that unlock the next phase of growth for our business.

Come join us if you’re excited about leading our nascent data science and predictive analytics efforts, and want to work side-by-side with engineering teams to have your work directly impacting patient care and driving the shift towards a more effective US healthcare system!

What you’ll do:

• Understand and prepare high quality datasets. Data science cannot exist without clean, well-understood data, and we want someone who can roll up their sleeves to do table stakes data engineering work. 
  • You’ll dig into new & existing data sets, be curious about business needs & edge cases, and deeply understand how data flows through our system.
  • You’ll accurately model data, clean it when necessary and ensure critical code you write is well-tested.
  • SQL expertise is a must, as is familiarity with DBT and data warehouses (we use Snowflake, but experience with others is fine).
• Perform thoughtful, quick analyses to enable important decisions. You’ll be at the forefront of understanding what makes our business tick, and you’ll be posed many questions for which no one yet has an answer.
  • You’ll need to thrive in ambiguity and decision making with imperfect or partial visibility.
  • You’ll need to be able to quickly zero in on the right questions to answer (even if that wasn’t what was asked) and then do the analyses necessary to unblock yourself and the team.
• Build production-ready statistical and predictive models. Your work will help us better model our provider & patient populations, and in some cases, predict what interventions we should deploy.
  • You’ll need to be comfortable with Engineering collaborations and what it means to move something from an offline ad-hoc insight to an online, automated system that impacts thousands of providers and millions of patients every day.
  • You’ll need to be opinionated about what excellent looks like when deploying insights and models into a live product. You’ll need to answer how we validate pre- and post- launch, and how we improve over time.
• Lead, collaborate and communicate well with others. You’ll be our primary expert in data science and machine learning techniques, and we’ll be looking to you to both do exceptional technical work and to bring others along.
  • You’ll sometimes need to teach and educate others on best practices for data science and predictive modeling.
  • You’ll need to proactively collaborate with multiple teams and translate among them to ensure your work lands successfully.
  • You’ll communicate clearly and effectively about what, how and why we’re making decisions in order to create trust in your team’s work.
• Get things done and advance our mission. We’re all here to help reshape the US healthcare system into something that delivers more value with lower costs. We want someone who understands this urgency and is equally inspired by the mission to get as much done as quickly as possible to help our providers and patients.

As Lead Data Scientist you should have:

• 10+ years of data science, analytics or machine learning experience
• Hands on experience with data engineering, predictive modeling and experimentation / causal inference methods
• Senior-level engineering & coding skills – you will be collaborating closely with engineers and contributing to important data pipelines and production systems
• Excellent communication skills, including the ability to explain technical analyses to non-technical audiences
• Advanced degree in data science / machine learning / statistics
• Although this is an individual contributor role, it requires leadership skills, so experience leading teams is a plus
• Healthcare experience is a plus

Who will love this job:

You are a builder, excited to be our first product-focused data science hire, and eager to shape and grow our capabilities.

• You get things done, and you love working in a dynamic, early stage environment.
• You understand, appreciate and enjoy the responsibility and accountability that comes with being assigned ownership over projects and their success.
• You are organized, proactive, principled and articulate, which makes you effective at driving cross-functional teams to align.
• You have high standards – you care about doing great work and about being an exceptional member of your team. You also expect this of others.
• You care about the mission, and want to spend your time on something that truly matters.

Pay:

We are considering candidates with differing levels of expertise for this position. Leveling and placement within the band will be based upon your relevant experience and performance in the interview process.  Stellar's bands are designed to allow for individual compensation growth within the role.  As such, new hires typically start at the lower end of the range.  Stellar rewards performance and outcomes - should you join the company, you will have the opportunity to grow your salary over time.

The salary range for the Lead Data Scientist is $175,000 - $220,000 and will be eligible for an annual performance based bonus and equity grant

Stellar reserves the right to change our compensation bands at any time. 

Perks & Benefits:

Stellar offers a carefully curated selection of wellness benefits and perks to our employees:

• Medical, Dental and Vision Benefits
• Unlimited PTO
• Universal Paid Family Leave
• Company sponsored One Medical memberships and Citibike memberships
• Medical Travel Benefits 
• A monthly wellness stipend that gives employees the freedom to choose where they spend their cash, whether it be on wellness, pet care, childcare, WFH items, or charitable donations
• Stock Options & a 401k matching program
• Career development opportunities like Manager Training, coaching, and an internal mobility program
• A broad calendar of company sponsored social events that for our in-office and remote employees

Diversity is the key to our success. Stellar Health is an equal opportunity employer and we are open to all qualified applicants regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, veteran status, or any other legally protected status.  

We believe that diverse teams -and the different identities, cultures, and life experiences our team members bring to the table- enable us to create amazing products, find creative solutions to interesting problems, and build an inclusive working environment. 

Stellar Health Employment Privacy Notice

At Stellar Health, your privacy and security as a job seeker is a priority no matter where you are in the interview process. As recruiting scams have become more prevalent, please take note of the following practices to ensure the legitimacy of any interaction with our team. 

• Please note that any communication from our recruiters and hiring managers at Stellar Health about a job opportunity will only be made by a Stellar Health employee with an @stellar.health email address. 
• Stellar Health does not utilize third-party agencies for recruitment services and does not conduct text message or chat-based interviews. Any other email addresses, agencies, or forums may be phishing scams designed to obtain your personal information. 
• We will not ask you to provide personal or financial information, including, but not limited to, your social security number, online account passwords, credit card numbers, passport information, and other related banking information until we begin onboarding activities, which will be coordinated by a member of the Stellar Health People Ops Team with an @stellar.health email address.  

If you are ever unsure whether you are in contact with a legitimate Stellar Health teammate, please contact people-team@stellar.health. If you believe you've been a victim of a phishing attack, please mark the communication as “spam” and immediately report it by contacting the U.S. Federal Trade Commission.