Data Science Architect

3 weeks ago

Preston, United Kingdom Hydrogen Group Full time

Data Science Architect

Hybrid role in Preston

Up to £69,000 per annum depending on experience and skills

Role Overview:
As a Data Science Architect, you will play a pivotal role in shaping and driving the adoption of Data Science, AI/ML, MLOps, and software modernization within the organisation. You will be responsible for defining processes, governance structures, and standards for the development and deployment of advanced data-driven products and solutions. Your work will involve close collaboration with the Data Science team and other stakeholders to ensure seamless integration and delivery of innovative solutions that align with business objectives.

Key Responsibilities:

  • Advocate and Educate: Effectively communicate the value and potential of Data Science, AI/ML, MLOps, and modern software practices to business stakeholders, ensuring alignment with organizational goals.
  • Establish Standards: Define and implement processes, governance frameworks, and standards for developing Data Science and AI/ML products, ensuring best practices and consistency across projects.
  • Architectural Leadership: Collaborate closely with the Data Science team to design architectural patterns, create high-level solution designs, and provide quality oversight for product delivery into the business.
  • Toolchain Implementation: Work with the Group IM&T team to research, select, and implement application toolchains that support the development, deployment, and maintenance of Data Science and AI/ML solutions, including their environments and infrastructure.
  • Documentation and Compliance: Ensure that all architectural and service documentation is meticulously created and maintained within the Data Science domain, adhering to the company's standards.
  • Solution Design: Develop high-level architectural designs for prioritized business needs, ensuring they meet derived business requirements and are consistent with enterprise architecture principles.
  • Interoperability: Guarantee that all architectural solutions are fully interoperable with existing systems within the Data Science domain and related domains, ensuring seamless integration and performance.



Required Skills and Experience:

  • Educational Background: Bachelor's degree in a relevant field such as Mathematics, Engineering, Computer Science, or other STEM disciplines.
  • Domain Expertise: Proven experience in the data domain, with a strong background in Data Science.
  • Data Modelling: Proficiency in data modelling, with the ability to design and implement robust data structures that support advanced analytics.



Preferred Qualifications:

  • TOGAF Certification: A TOGAF certification is highly desirable, demonstrating expertise in enterprise architecture frameworks.



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