Lead and architect advanced analytics and machine learning solutions within the Microsoft cloud ecosystem to support strategic decisions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack, ensuring alignment to enterprise data architecture and governance standards.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
Principal‑level data scientist responsible for architecting, delivering, and governing enterprise‑grade advanced analytics and machine learning solutions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations. This position is not eligible for bonus or incentive compensation.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions
Own end‑to‑end analytical solution lifecycle
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility
Design analytics solutions natively within the Microsoft cloud analytics stack
Partner closely with executive stakeholders, data engineering leaders, and platform owners
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
Develop, maintain, and optimize Python pipelines for data ingestion, OCR processing, text extraction, cleaning, normalization, and deduplication.
Run and monitor large-scale batch processing jobs, investigate failures, and implement reliable retry and recovery mechanisms.
Build automated quality checks to identify missing or corrupted files, incomplete OCR outputs, duplicate content, formatting issues, and metadata inconsistencies.
Prepare training-ready datasets through filtering, text segmentation, tokenization, and conversion into agreed data formats.
Manage bulk uploads, downloads, and synchronization between local processing environments and Azure storage; verify transfer completeness and data integrity.
Lead data science efforts on high-priority initiatives, build and evaluate machine learning models, and mentor junior team members.
Compensation
The base salary compensation range being offered for this role is $116,000 - $141,000 USD annually.
Responsibilities
Build models end to end
Develop prototypes and products
Lead data science efforts on anomaly detection, forecasting, and predictive modeling
Partner with AI Engineers and Developers
Communicate findings and translate results into actionable business recommendations
Requirements
Bachelor's degree in Computer Science, Information Technology, Data Science, Mathematics, Statistics, Economics, Business Administration, or a related field
The Sr Staff AI Security Engineer serves as the primary architect and guardian of the Artificial Intelligence ecosystem, responsible for the end-to-end security of AI architectures specifically within the Azure AI stack.
Compensation
Base Salary Range: $172,780 to $225,720 annually
Responsibilities
Design and implement secure-by-design architectures for the entire AI lifecycle, including data ingestion, model training, fine-tuning, and inference.
Lead the security configuration for Azure OpenAI Studio, Azure AI Foundry, and Azure AI Search.
Develop and deploy security controls, including prompt injection mitigations, rate limiting, and content filtering.
Securely implement and oversee Model Context Protocol (MCP) to facilitate safe communication between AI models and local/remote data sources.
Establish and maintain AI security standards based on global frameworks (e.g., NIST AI RMF, ISO/IEC 42001, OWASP Top 10 for LLMs).
Design, develop, deploy, and support cloud-native applications within the Microsoft Azure ecosystem.
Compensation
Compensation: $117,000 - $147,000 per year
Responsibilities
Design, develop, deploy, and support cloud-native applications within the Microsoft Azure ecosystem.
Build AI-powered solutions using Azure OpenAI, Azure AI Services, Azure Machine Learning, and approved LLM technologies.
Create secure integrations between Azure applications, Symitar core systems, and enterprise platforms through APIs and modern integration technologies.
Drive intelligent automation initiatives that improve efficiency, user experiences, and operational effectiveness.
Develop and maintain CI/CD pipelines and deployment automation using Azure DevOps.
Requirements
Bachelor's degree in Computer Science, Information Systems, Software Development, or a related field (or equivalent experience).
Nice to have: Experience developing AI-enabled applications and intelligent automation solutions.
Nice to have: Familiarity with Azure OpenAI, Azure AI Services, and machine learning technologies.
Nice to have: Experience with Agile/Scrum environments.
Nice to have: Knowledge of Symitar/Episys or other core banking platforms.
Support enterprise AI/ML architecture initiatives, governance frameworks, and agentic AI capabilities across federal modernization programs.
Compensation
Salary Range: $120k - $155k
Responsibilities
Support AI/ML architecture design and engineering activities across enterprise architecture and modernization initiatives.
Assist in developing and maintaining enterprise AI architecture baselines, target-state architectures, and transition roadmaps.
Contribute to solution architecture efforts for AI-enabled systems, integrating cloud-native services and advanced analytics platforms.
Support the development and maintenance of AI model governance frameworks, including model lifecycle management, risk assessments, and compliance monitoring.
Assist in designing scalable data pipeline architectures to support AI/ML training, inference, monitoring, and continuous improvement.
Requirements
Bachelor’s degree in Computer Science, Engineering, Data Science, or related field
Master’s degree in Computer Science, Engineering, Information Technology, or related discipline
Nice to have: Master’s degree
Nice to have: AI/ML platforms and services including Azure AI, Azure Machine Learning, Amazon SageMaker, OpenAI services
Nice to have: Generative AI and large language model (LLM) technologies
McKesson is seeking a Sr. Specialist, Machine Learning Engineering to design, build, and scale production-grade AI, machine learning, and generative AI solutions that deliver meaningful business impact. The role involves leading development of scalable ML platforms, production pipelines, model deployment frameworks, and MLOps capabilities.
Compensation
Our Base Pay Range for this position is €72,000 - €120,000
Responsibilities
Lead the design, development, deployment, and operation of enterprise-scale AI/ML and LLM solutions.
Build and productionize machine learning pipelines using Azure Machine Learning, Azure Databricks, and cloud-native services.
Establish and enhance MLOps and LLMOps practices including CI/CD, model versioning, automated testing, monitoring, and governance.
Develop scalable deployment architectures using containerization, infrastructure as code, and automation frameworks.
Partner with data scientists and product teams to transition prototypes into reliable production systems.
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