Data Scientist Lead
About The Position
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!
Requirements
- 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.
Nice To Haves
- Experience with real-time systems, RTLS, or healthcare data
- Knowledge of healthcare regulations and EHR systems (Epic, Cerner, Meditech)
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
