Data Scientist Lead

About Kontakt.io 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 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. 🚀