Data Science Architect, Contract New United Kingdom

66degrees is an end-to-end AI transformation partner that guides enterprises from complex business challenges to clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity becomes clarity, and AI becomes an engine for growth. Our ultimate vision is to be the catalyst for a future where every business operates as an intelligent enterprise, with autonomous systems unlocking human potential. At 66degrees, we believe in thriving through challenges and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.

Overview of Role

A 66degrees AI/ML Architect is a multifaceted professional responsible for leading the technical development and implementation of AI/ML solutions, managing client relationships, and ensuring the delivery of business value. They serve as the primary technical point of contact for clients and act as the bridge between them and our delivery team. A 66degrees AI/ML Architect is also a strategic partner to clients, ensuring that AI/ML projects are successfully executed and deliver significant business value. They balance technical expertise with strong client management and project oversight skills. Additionally, they identify and inform about upselling opportunities within their client engagements to continue growing our relationship with the client.

Duration: 4+ Months

Responsibilities

• Project Leader, Trusted Advisor, Thought Leader and Mentor.
• Gathering Requirements: Engaging with clients to understand their needs and requirements for the solution.
• Designing Solutions: Creating tailored solutions that meet client specifications and business goals.
• Client Communication: Maintaining clear and effective communication with the client throughout the project lifecycle.
• Identifying and Mitigating Risk: Monitoring the project to ensure it stays within the defined scope and managing any changes or expansions.
• Identifying Resource Issues: Recognizing and escalating any resource constraints or issues that could impact project delivery.
• Building Sprints: Planning and organizing work into sprints alongside the DM to ensure timely and efficient delivery of the project.
• Bridging Gaps: Facilitating collaboration between different teams to ensure seamless integration and delivery of the AI/ML solution.
• Ensuring Ethical AI: Implementing ethical AI practices, including fairness, interpretability, privacy, and safety and security.

In addition to these technical responsibilities, the architect is tasked with managing client relationships, ensuring client satisfaction, and delivering tangible value. They are not just technical leaders but also project managers and client advocates, ensuring the successful implementation of AI/ML projects.

AI/ML architects strive to become trusted advisors to their clients. This involves:

• Building Trust: Establishing strong, trust-based relationships with clients.
• Ensuring Value: Ensuring that AI/ML projects deliver significant business value and meet client objectives.
• Providing Expertise: Offering expert advice and insights on AI/ML strategies and solutions.
• Identifying Opportunities: Recognizing and communicating to sales upselling opportunities to deliver additional value to clients.

Thought Leader

As a Thought Leader, AI/ML architects lead the technical competencies of this team:

• Staying Informed: Keeping abreast of the latest research, trends, and innovations in AI/ML.
• Professional Development: Continuously improving their own skills through courses, certifications, and industry conferences.
• Fostering Innovation: Promoting a culture of innovation within their team by encouraging new ideas and experimenting with cutting‑edge technologies.
• Tool and Technology Evaluation: Assessing and integrating the latest tools and technologies to enhance AI/ML solutions and improve project outcomes.
• Knowledge Sharing: Sharing expertise and insights with their team and the broader organization to foster a learning environment and keep everyone updated on industry trends.

By emphasizing continuous learning, innovation, and leadership in AI/ML, architects ensure their solutions remain at the forefront of technology, delivering maximum value to clients and maintaining a competitive edge in the industry.

An architect's role extends beyond technical expertise; it includes mentoring engineers and facilitating knowledge sharing across the team and organization. By nurturing team members and fostering collaboration, architects ensure continuous growth and success in AI/ML initiatives. Architects also significantly contribute to the feedback loop with managers, providing valuable insights that help managers refine their coaching strategies and tailor development plans to ensure each team member receives the necessary support for growth and success.

Qualifications

• 6+ years of experience with data science.
• Deep practical execution across complex multi-variable linear/logistic regression, time-series forecasting, and structural classification models.
• Experience with large-scale multi-dimensional clustering, propensity segmenting, and custom anomaly detection.
• Hands‑on model customization utilizing frameworks like PyTorch, TensorFlow, Keras, or specialized toolsets.
• Proven experience designing autonomous, state‑managed agentic workflows.
• Practical, production‑level code deployment utilizing advanced multi‑agent frameworks.
• Hands‑on competency implementation with Model Context Protocol (MCP) patterns.
• Proven experience taking models completely from POC to enterprise deployment.
• Strong software engineering fundamentals with expert‑level Python and SQL.
• Deep immersion with Docker, Kubernetes, and setting up Git‑backed testing frameworks.
• Deep experience extracting, cleansing, and transforming fragmented, massive data streams into scalable, unified data estates.
• Ability to track changing business requirements and deliver quality solutions both independently and with teams of varying skill sets.
• Bachelor’s degree in Data Science, Computer Science or similar.
• Experience with Google Cloud Platform.

66degrees is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, religion, sex, gender, gender identity, national origin, age, weight, height, marital status, sexual orientation, veteran status, disability status or other legally protected class.