Data Scientist Lead

About Kontakt.io http://Kontakt.io

Kontakt.io http://Kontakt.io is building the platform that care operations run on.

We reduce waste, cut costs, and improve throughput in hospitals by automating and orchestrating clinical workflows. Using AI, real-time location data (RTLS), and deep EHR integration, our platform enables care teams to operate with real-time intelligence and financial discipline.

Trusted by leading U.S. health systems including HCA, Sutter Health, AdventHealth, Trinity Health, and the U.S. Department of Veterans Affairs — and backed by Goldman Sachs — we are scaling rapidly toward the next phase of durable, disciplined hypergrowth.

As a Data Science Lead, you will play a pivotal role in designing, developing, and deploying machine learning models that drive AI-powered automation across healthcare operations. You will own end-to-end ML lifecycle management, ensuring operational excellence, measurable business impact, and collaboration with cross-functional teams. Your work will enable hospitals and healthcare facilities to deliver better, faster, and more cost-effective care.If you’re passionate about building impactful ML solutions, leading data science teams, and transforming care delivery operations, join Kontakt.io http://Kontakt.io and help us redefine the future of healthcare!

Responsibilites

• Own the full lifecycle of assigned ML models — from ideation to deployment and post-launch validation.
• Translate business goals into measurable data science objectives (e.g., improve workflow efficiency or reduce operational latency).
• Design and execute robust A/B or interleaved tests to quantify model impact; define success metrics before deployment.
• Deliver production-ready, well-documented code following internal engineering standards (testing, CI/CD, peer review).
• Package and deploy models as services (APIs, microservices), treating deployment as an integral part of development.
• Maintain operational reliability, scalability, and performance of all owned models and pipelines.
• Build dashboards and alerts for model health, drift detection, and SLA compliance.
• Continuously monitor for degradation, bias, or data drift; proactively resolve issues.
• Participate in on-call rotation for ML systems; enable team to serve as primary responder for incidents related to owned models and data services.
• Lead root cause analysis (RCA) within 48 hours of production incidents and document remediation actions.
• Serve as the internal subject-matter expert for your domain (e.g., patient journey, asset utilization).
• Partner with Product, Engineering, and Leadership to communicate insights, model limitations, and roadmap priorities.
• Identify high-value data sources and upstream improvements to improve model outcomes or enable new capabilities meaningfully.
• Ensure all initiatives are tied to clear metrics or business KPIs.

What You Bring

• Proven leadership experience with the ability to drive technical strategy while mentoring a high-performance Data Science and ML Engineering team.
• 10+ years of experience in Data Science, Machine Learning, or related roles.
• Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, or Scikit-learn).
• Experience with production ML systems, including model deployment, monitoring, and lifecycle management.
• Familiarity with cloud platforms (AWS) and scalable ML infrastructure.
• Strong understanding of data engineering, feature engineering, and model evaluation metrics.
• Experience with real-time systems, RTLS, or healthcare data
• Knowledge of healthcare regulations and EHR systems (Epic, Cerner, Meditech)

• Ready to Build the Future of Healthcare?
• Apply now and help to build the platform that care operations run on. 🚀