Head of Data Science and Machine Learning Engineering
📍 Northern Virginia | 💼 Executive Leadership Role

A leading technology-driven organization in Northern Virginia is seeking a visionary and hands-on leader to serve as its Head of Data Science and Machine Learning Engineering. This high-impact role offers the opportunity to own the entire AI/ML lifecycle—from research and algorithmic innovation to scalable production deployment—while leading integrated Data Science and Machine Learning Engineering teams.

As a key member of the technology leadership team, you will define and execute the strategic AI vision, directly influencing product innovation, customer experience, and competitive differentiation.

What You’ll Do

Team Leadership

• Lead and mentor high-performing Data Science and Machine Learning Engineering teams.
• Foster a collaborative culture focused on excellence, accountability, and innovation.
• Define operational models that optimize delivery speed, quality, and scalability.

Strategic Ownership

• Own the end-to-end machine learning lifecycle: ideation, development, deployment, monitoring, and maintenance.
• Align AI/ML strategy with product and business goals.
• Drive an R&D agenda focused on advanced modeling techniques and agentic systems.

Technical Delivery

• Architect and scale MLOps infrastructure for robust, automated model deployment.
• Provide hands-on leadership in developing models using deep learning, embeddings, neural networks, and GNNs.
• Utilize AWS Bedrock, SageMaker, TensorFlow, and PyTorch to build scalable AI solutions.
• Stay ahead of emerging trends in ML, AI, and GenAI.

Communication & Evangelism

• Partner with executive leadership to communicate AI strategy across the organization.
• Represent the company at industry events and customer engagements.
• Translate complex technical concepts for diverse audiences.

What You Bring

Leadership & Communication

• Proven ability to lead both research-focused and production-focused teams.
• Strong communication and presentation skills; comfortable engaging with clients, analysts, and media.
• A collaborative mindset and ability to work cross-functionally with engineering, product, and GTM teams.
• Passion for continuous learning and innovation.

Technical Expertise

• Deep knowledge of modern ML techniques: gradient boosting, Bayesian models, causal inference, deep learning, embeddings, GNNs.
• Hands-on experience with MLOps tools and principles (CI/CD for ML, model registries, feature stores).
• Strong software engineering and architectural skills.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and scikit-learn.
• Experience with AWS AI/ML services, especially Bedrock and SageMaker.
• Familiarity with agentic workflows is a plus.

Bonus Experience

• Background in consumer data, ad-tech, or mar-tech.
• Domain expertise in health, finance, consumer goods, politics, or advocacy.

If you’re a strategic thinker with a passion for data and innovation, and ready to shape the future of enterprise-level machine learning systems, we’d love to connect.