Data Scientist Lead

Data Science Lead

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!

Responsibilities

1. Own the full lifecycle of assigned ML models — from ideation to deployment and post-launch validation.
2. Translate business goals into measurable data science objectives (e.g., improve workflow efficiency or reduce operational latency).
3. Design and execute robust A/B or interleaved tests to quantify model impact; define success metrics before deployment.
4. Deliver production-ready, well-documented code following internal engineering standards (testing, CI/CD, peer review).
5. Package and deploy models as services (APIs, microservices), treating deployment as an integral part of development.
6. Maintain operational reliability, scalability, and performance of all owned models and pipelines.
7. Build dashboards and alerts for model health, drift detection, and SLA compliance.
8. Continuously monitor for degradation, bias, or data drift; proactively resolve issues.
9. Participate in on-call rotation for ML systems; enable team to serve as primary responder for incidents related to owned models and data services.
10. Lead root cause analysis (RCA) within 48 hours of production incidents and document remediation actions.
11. Serve as the internal subject-matter expert for your domain (e.g., patient journey, asset utilization).
12. Partner with Product, Engineering, and Leadership to communicate insights, model limitations, and roadmap priorities.
13. Identify high-value data sources and upstream improvements to improve model outcomes or enable new capabilities meaningfully.
14. 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)

Logistics, Perks & Benefits

• Built for collaboration - our team a hybrid schedule of 3 days/week minimum from our New York City office
• Equity in a high-growth company scaling toward $400M+ ARR and backed by leading investors
• Full health, dental, and vision coverage, a 401k, paid time off, paid parental leave and all the tools you need to do your best work
• Autonomy to solve meaningful problems with work that ships quickly and makes a difference

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