Data Science Lead

Mars
Slough
1 month ago
Applications closed

Related Jobs

View all jobs

Data Science Lead / Hybrid Manchester / Up To £90,000

Data Science Lead

Data Analytics & Data Science Lead

TikTok Shop - Data Science Lead, Governance & Experience, EMEA

Associate Director, Data Science and Innovation

Senior Data Scientist

Senior Talent Acquisition Specialist @ Mars | Global Leadership Recruitment | Digital, Data & Technology | Driving Digital Transformation & Growth

The Chief Data Office (CDO) is a Mars Wrigley program that leverages data and insights to address key business challenges, driving quality growth and operational excellence.

CDO enables connected insights across the Mars Snacking ecosystem, equipping associates with the right data, tools, and capabilities to make informed decisions that maximize value and create meaningful impact for consumers, customers, and the business.

This role will be instrumental in driving AI and data science initiatives within Mars Snacking, focusing on demand and supply chain analytics. The position requires strong leadership in managing AI teams, developing scalable and high-quality AI solutions, and collaborating with business stakeholders to align analytics strategies with company objectives. The ideal candidate will have extensive experience in AI, machine learning, and advanced analytics, with a strong understanding of product management principles. They will ensure compliance with governance policies while fostering innovation in AI-driven decision-making. This role offers the opportunity to work in a dynamic environment, leveraging cutting-edge technologies to drive business impact.

What are we looking for?

  • 7+ years of experience in a quantitative role, preferably in the CPG or retail industry.
  • 4+ years of experience leading teams of data scientists, product analysts, or data analysts.
  • Proven ability to deliver AI/Data Science solutions in fast-paced, agile environments using scalable, reusable code and models.
  • Strong collaboration with business leaders to identify challenges and translate them into actionable, data-driven solutions.
  • Adaptability, problem-solving skills, and a growth mindset to thrive in dynamic environments and build high-performing teams.
  • Deep expertise in demand and supply chain KPIs and analytical solutions within the CPG/Retail industry.
  • Understanding of product management principles, including product definition, roadmap development, and commercialization.
  • Customer-centric approach to drive value creation, adoption, and usage within an internal stakeholder base.
  • Strategic thinking, problem-solving, and innovation to anticipate and navigate challenges.
  • Compliance with analytics standards, tailoring methodologies for ML, AI, and descriptive analytics.
  • Ability to translate business needs into analytical frameworks with strong communication skills.
  • Hands-on experience in advanced analytics and ML techniques, including NLP and time-series analysis, with a willingness to coach data scientists.
  • Working knowledge of ML Ops and DevOps frameworks.
  • Familiarity with Microsoft Azure tech stack, including Azure Data Factory, Synapse Analytics, and Databricks.

What will be your key responsibilities?

  • Mars Principles: Embody and uphold the Five Principles of Mars, Inc. within the team and personal conduct.
  • Stakeholder Engagement & Thought Leadership: Collaborate with Mars Snacking D&A leadership, product owners, and managers to shape and execute the AI and analytics strategy, aligning with business goals and data-driven decision-making.
  • Team & Resource Management: Build and lead multi-location AI teams, overseeing the full model development lifecycle from ideation to deployment and continuous optimization, while managing resources effectively.
  • Data Governance & Compliance: Ensure AI solutions adhere to governance policies, ethical AI principles, and privacy regulations while implementing best practices.
  • AI & Data as a Product: Drive the development of scalable, secure, and high-quality AI models and data assets that address business challenges and enhance decision intelligence.
  • Solution Ideation & Development: Lead a team of data scientists in creating cutting-edge AI and machine learning solutions tailored to business needs, ensuring accuracy, scalability, and impact.

What can you expect from Mars?

  • Work with diverse and talented Associates, all guided by the Five Principles.
  • Join a purpose driven company, where we’re striving to build the world we want tomorrow, today.
  • 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.

Seniority level

  • Associate

Employment type

  • Temporary

Job function

  • Analyst and Information Technology
  • Manufacturing

#J-18808-Ljbffr

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.

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

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.