Data Scientist Lead

KONTAKT LLC

United States

about 2 months ago

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Role details

Contract type

Permanent contract

Employment type

Part-time (≤ 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

jobs.ashbyhq.com

Tech stack

Cerner Application Programming Interfaces (APIs) Amazon Web Services Cloud Computing Continuous Integration Data as a Services Information Engineering Python (Programming Language) Machine Learning Tensorflow Real Time Systems Feature Engineering

+7 more

EHR Systems Pytorch Model Validation Scikit Learn Machine Learning Operations Meditech Microservices

Job description

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!
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

Requirements

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