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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Scientist - **Company:** ALTAK GROUP INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $145,600.0 - $158,080.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Big Data, Cloud Computing, EHealth, Monitoring of Systems, Interoperability, Python (Programming Language), Machine Learning, Operational Data Store, Performance Tuning, Software Architecture, Tensorflow, Azure Machine Learning, Feature Engineering, Chatbots, Data Ingestion, Pytorch, Fast Healthcare Interoperability Resources, Snowflake, Apache Spark, IT Architecture, Electronic Medical Records, Generative AI, Scikit Learn, Kubernetes, Health Level Seven International, Machine Learning Operations, Virtual Agents, Databricks - **Published:** July 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=a24925c279e505a7 ## About the Role · 7+ years of experience in data science, with recent experience in a Lead Data Scientist or similar senior role. · Hands-on experience designing and deploying ML models in production environments. · Solid understanding of AI architecture concepts, including scalable ML systems, MLOps, and cloud-based deployments. · Experience implementing Generative AI solutions, including RAG-based chatbot applications. · Proficiency in Python and common ML libraries (e.g., scikit-learn, TensorFlow, PyTorch). · Experience with SǪL and big data technologies (e.g., Spark, Databricks, Snowflake). · Strong understanding of data modeling, statistics, and machine learning algorithms. · Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders · Experience designing AI solutions leveraging AWS services and Tech Stack · Proficient in managing cross-domain architecture solutions and impacts. · Expertise with domain related architecture frameworks, methods and tools. Preferred Ǫualifications · Strong experience working in the healthcare domain (payer, provider, life sciences, digital health, or health tech). · Prior experience collaborating closely with or acting as an AI Architect on enterprise-scale solutions. · Experience building Agentic AI solutions and developing autonomous AI agents. · Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Azure ML). · Familiarity with NLP, computer vision, or generative AI use cases in healthcare. · Knowledge of healthcare interoperability standards such as HL7, FHIR, or ICD codes. · Experience leading cross-functional teams in a contract or consulting environment., * Bachelor's (Required), * RAG Pipelines: 3 years (Required) * Leadership: 3 years (Required) * Data science: 7 years (Required) * Machine learning: 7 years (Required) ## Description We are seeking an experienced Lead Data Scientist with hands-on exposure to AI architecture. This role requires a senior individual who has led data science initiatives end-to-end while collaborating closely with engineering, product, and AI architecture teams to design scalable, production-ready AI solutions. Key Responsibilities · Lead the design, development, and deployment of advanced data science and machine learning solutions within the healthcare domain. · Act as a technical lead, guiding data scientists and collaborating with AI Architects to ensure scalable, secure, and compliant AI systems. · Architect and optimize end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, and deployment. · Work with structured and unstructured healthcare data such as EHR/EMR, claims, clinical notes, imaging metadata, and operational data. · Partner with stakeholders to define problem statements, success metrics, and data strategies aligned with clinical and business goals. · Ensure models comply with healthcare regulations and standards, including HIPAA and data privacy best practices. · Evaluate and recommend tools, frameworks, and cloud-based solutions for ML and AI workloads. · Oversee model monitoring, performance tuning, explainability, and governance in production environments. · Contribute to AI strategy, solution roadmaps, and architectural decisions alongside AI and platform teams. ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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