Analytics Director - Data Science

Mars Wrigley Confectionery UK (SLO, WAL, ISB & PAD)
united kingdom
4 days ago
Create job alert

We are seeking a highly skilled and visionary Director of Data Platforms and Architecture to lead the design, development, and governance of our enterprise–wide Snacking data platform ecosystem. This individual will be responsible for driving platform strategy, fostering innovation, and ensuring robust data architecture that empower multiple products and capabilities to power business decisions, scalability, and operational excellence. As a strategic leader, the Director of Data Platforms and Architecture will oversee the implementation and optimization of cutting–edge data technologies & solutions, establish best practices in data platforms and governance, and provide technical leadership to multidisciplinary teams. You will work closely with stakeholders across business, IT, and analytics teams to align data architecture with organizational goals, enabling seamless data acquisition and advanced analytics capabilities. Develop and drive the long–term vision for enterprise data platforms and architecture, ensuring alignment with organizational goals and priorities. Collaborate with C–level executives and business leaders to identify opportunities for leveraging data as a strategic asset. Data Platform Oversight: Oversee the design, implementation, and maintenance of modern data platforms, including cloud–native solutions, data lakes, data warehouses, and real–time processing systems. Ensure scalability, reliability, and high availability of the data ecosystem to support growing business needs. Define and implement enterprise data architecture standards, including data modeling, integration, and API frameworks. Optimize workflows and pipelines to ensure efficient and secure data ingestion, processing, storage, and access. Foster a data–driven culture by ensuring architecture supports self–service analytics and business intelligence tools. Data Governance & Security: Establish and enforce robust data governance practices, ensuring compliance with regulatory requirements and company policies. Partner with IT security teams to implement secure–by–design data architectures that protect sensitive information and mitigate risks. Lead and mentor a team of data architects, platform engineers, and data governance professionals. Stay abreast of emerging technologies, tools, and industry trends in data platforms, AI/ML, and big data. Proactively evaluate and recommend new technologies that enhance data capabilities and drive business innovation. Partner with IT, analytics, and business teams to identify data needs and translate them into actionable platform solutions. Advocate for data democratization by enabling access to clean, high–quality data for decision–making. Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field. ~10+ years of experience in data engineering, architecture, or platform management roles, with 5+ years in leadership positions. ~ Expertise in modern data platforms (e.g., Azure, AWS, Google Cloud) and big data technologies (e.g., Strong knowledge of data governance frameworks, regulatory compliance (e.g., GDPR, CCPA), and data security best practices. ~ Proven experience in enterprise–level architecture design and implementation. ~ Hands–on knowledge of database systems (SQL/NoSQL), ETL/ELT processes, and data modeling techniques. ~ Ability to work in fast–paced, agile environments and balance long–term strategy with short–term execution. Certifications in cloud platforms (AWS Certified Data Analytics, Azure Data Engineer, etc.). Experience with AI/ML technologies and data science platforms. Familiarity with DevOps, CI/CD pipelines, and Infrastructure as Code (IaC). Best–in–class learning and development support from day one, including access to our in–house Mars University. An industry competitive salary and benefits package, including company bonus. Mars is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need assistance or an accommodation during the application process because of a disability, it is available upon request.

Related Jobs

View all jobs

Group Director, Business Intelligence & Customer Master (Basé à London)

Group Director, Business Intelligence & Customer Master (Basé à London)

Commercial Director - Data Analytics Product

Commercial Director - Data Analytics Product

Commercial Director - Data Analytics Product

Commercial Director - Data Analytics Product

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.