Data Scientist 1

About ShiftKey

ShiftKey is a platform that is disrupting the way healthcare facilities find licensed and certified professionals to fill available shifts. Leveraging marketplace dynamics and deep industry knowledge, the company is playing a vital role in mitigating America’s healthcare staffing shortages, enabling direct connections between facilities and healthcare professionals. By offering the opportunity to work as much or as little as they choose and putting the power back into the hands of healthcare workers, ShiftKey is bringing more licensed professionals back into the workforce, a solution that is solving a major crisis in healthcare. For more information, visit www.ShiftKey.com.

The role

We’re looking for a Data Scientist I to join our Data, Analytics & AI team. You’ll help build predictive analytics and AI capabilities that directly shape how ShiftKey connects facilities and healthcare professionals. This is a hands-on role where you’ll take over and enhance existing models while also helping us expand our machine learning and statistical modeling foundations. You’ll report directly to our VP of Data, Analytics & AI, and collaborate with a Senior Data Scientist, Analysts, Engineers, Product Managers, and business stakeholders.

Where you’ll work

To be considered for this position, you must be located in the United States. You can choose between remote work and working from one of our offices in Austin, Dallas, or Cleveland.

What you’ll be doing

• Develop, improve, and deploy machine learning models that power ShiftKey’s marketplace (e.g., shift scoring, last-minute pricing).

• Work on both greenfield and existing projects, bringing fresh ideas to improve our predictive and prescriptive analytics.

• Partner with cross-functional teams to translate business problems into data science solutions.

• Evaluate model performance, run experiments, and design testing frameworks to ensure accuracy and impact.

• Explore new data sources and approaches to enhance our AI capabilities.

• Contribute to model deployment and monitoring in cloud environments (AWS preferred).

What you’ll need

• ~2 years of experience as a data scientist (or equivalent) with proven impact.

• Strong programming skills in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.) and solid SQL.

• Understanding of statistical modeling and experimentation techniques; exposure to deep learning and generative AI is a plus.

• Experience working with AWS (or Azure/GCP) and an interest in learning MLOps practices.

• Strong communication skills - you can explain complex ideas to both technical and non-technical audiences.

• Comfortable working in smaller, collaborative teams where you’ll have a direct impact.

• Bonus: familiarity with BI tools like Looker or Tableau (not for dashboarding, but for deeper data analysis).

Perks of working for ShiftKey

• Inclusive and collaborative work environment where all voices are valued.

• Hybrid-friendly office spaces designed to be fun and engaging.

• Comprehensive health, vision, and dental coverage.

• Benefits begin on your first day.

• Generous PTO and company-paid holidays, including flexible floating holidays.

• 100% 401(k) employer match up to 6%.

• Paid parental leave.

• Wellness support, including access to mental health resources.

#LI-Remote

Our Commitment to Diversity

ShiftKey is an equal opportunity employer and is committed to embracing diverse and individual perspectives shaping our culture and contributing to the solutions that transform the world. We actively work to create an inclusive environment for employees to thrive. 

EEO Statement

ShiftKey does not discriminate based on race, religion, color, sex, gender, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by applicable law. All employment is decided based on qualifications, merit, and business needs.  ShiftKey is committed to providing reasonable accommodation to applicants with a mental or physical disability, please contact: [email protected]