Director of Data Science
New
United StatesFull-TimeDirector
Salary168,400 - 252,600 USD per year
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Job Details
- Experience
- 12+ years of experience delivering enterprise technology solutions; 7+ years of experience in solution architecture and technical leadership
- Required Skills
- AgileMachine LearningMicrosoft Power BIAzureData scienceSparkDatabricksMLOpsGenerative AI
Requirements
- 12+ years of experience delivering enterprise technology solutions within cloud engineering, software development, DevOps, or data and analytics environments.
- 7+ years of experience in solution architecture and technical leadership across multi-team or enterprise-scale programs.
- Strong expertise in data science, machine learning, Azure cloud services, and modern data platforms including Azure ML, Databricks, Synapse, Fabric, Spark, and Power BI.
- Deep understanding of AI technologies including generative AI, retrieval-augmented generation (RAG), prompt orchestration, and AI-assisted development workflows.
- Proven experience designing scalable data architectures, governance models, automation strategies, and enterprise-grade cloud modernization solutions.
- Strong consulting and stakeholder management skills with the ability to influence executives, communicate complex concepts clearly, and drive strategic outcomes.
- Experience leading remote or distributed teams while maintaining alignment, engagement, and delivery excellence across time zones.
- Strong background in Agile delivery practices, architectural governance, quality engineering, and enterprise-scale delivery management.
- Relevant Azure, Databricks, AI, or cloud architecture certifications are strongly preferred.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field preferred.
Responsibilities
- Lead architecture strategy and execution for large-scale Azure modernization, AI, and data transformation programs across multiple teams and client environments.
- Oversee and mentor managers, architects, and engineering teams, fostering a culture of collaboration, accountability, inclusion, and continuous improvement.
- Develop scalable cloud, analytics, machine learning, and MLOps frameworks that support business goals, operational efficiency, and long-term maintainability.
- Guide cross-functional discovery sessions, architecture reviews, governance processes, and technical decision-making across enterprise programs.
- Drive adoption of AI-assisted engineering practices, automation strategies, CI/CD standards, and observability frameworks to improve delivery quality and speed.
- Partner with executive stakeholders to define modernization roadmaps, align delivery priorities, and communicate technical strategies to both technical and non-technical audiences.
- Support business growth through client relationship development, technical solution leadership, opportunity qualification, and proposal development.
- Create reusable assets, reference architectures, playbooks, and accelerators that improve scalability, consistency, and delivery efficiency across teams.
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