Analytics Manager

C5i
Leeds
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst - Graduate

Business Intelligence and Reporting Analyst

Analytics Engineering Manager

Product Manager

IT Project Manager

Program manager - Data Analyst

About C5i

C5i is a pure-play AI & Analytics provider that combines the power of human perspective with AI technology to deliver trustworthy intelligence. The company drives value through a comprehensive solution set, integrating multifunctional teams that have technical and business domain expertise with a robust suite of products, solutions, and accelerators tailored for various horizontal and industry-specific use cases. At the core, C5i’s focus is to deliver business impact at speed and scale by driving adoption of AI-assisted decision-making.


C5i caters to some of the world’s largest enterprises, including many Fortune 500 companies. The company’s clients span Technology, Media, and Telecom (TMT), Pharma & Lifesciences, CPG, Retail, Banking, and other sectors. C5i has been recognized by leading industry analysts like Gartner and Forrester for its Analytics and AI capabilities and proprietary AI-based platforms.


Global offices

United States | Canada | United Kingdom | United Arab of Emirates | India


Job Summary

We are seeking a highly skilled Analytics Manager with 8–10 years of experience in analytics, specifically in Revenue Management and Pricing analytics. The ideal candidate will have excellent leadership skills, be highly organized, and possess exceptional problem-solving abilities.

In this role as a Analytics Manager, you will be bridging the gap between business and analytics teams. You will collaborate with Business Product Owners, Analytics Teams, and Cross-Functional Partners to define key business problems, success criteria, drive product lifecycle and transform data-driven insights into strategic actions. You will be responsible for ensuring that analytical solutions align with business needs in Pricing Strategy, Trade Promotions, Revenue Optimization, and Market Insights.


Job Responsibilities

  • Business Understanding & Translation:Act as a liaison between business teams and data analytics teams to ensure alignment on Revenue Management objectives aligned with business vision, priorities and goals.Partner with business product owner to deliver Revenue Management D&A capabilities to drive & embed top quartile Promotion & Trade terms
  • Project Management: Lead NRM, SRM, and Pricing-related projects,defining scope, objectives, and deliverables in collaboration with stakeholders. Spearhead the D&A delivery of a comprehensive product strategy for the domain
  • Pricing & Revenue Analytics: Identify pricing, promotion, and assortment opportunities to optimize revenue streams. Drive insights on Price Elasticity, Promotional Effectiveness, Mix Optimization, and Trade Investment and recommend optimization strategies for ROI improvement
  • Stakeholder Collaboration: Work closely with Sales, Marketing, Finance, and Data Science Teamsto align on revenue growth strategies. Collaborate with cross-functional teams to design and implement analytics solutions that scale and are aligned with product objectives set out in the roadmap
  • Data Interpretation: Translate complex analytical outputs (e.g., Market Mix Models (MMM), Price Elasticity Models, and ROI of Promotions) into business-friendly insights
  • Performance Monitoring: Track KPIs related topricing strategies, promotional impact, and revenue growthto ensure continuous improvement
  • Presentation & Reporting: Create clear, impactful reports and presentations for senior leadership to influence pricing and promotion decisions
  • Training & Enablement: Educate stakeholders on how to interpret and leverage analytics to drive revenue growth


Minimum Requirements

  • Bachelor’s/Master’s degree in Business Administration, Economics, Finance, Data Science, or a related field
  • 8+ years of experience in a Business Translator/Consultant, Pricing, NRM, or SRM role within the CPG or Retail industry
  • CPG and Retailer knowledge, including knowledge of, and experience using key external third-party data sources including, first-party data, and Associates surveys
  • Proven Track Record of Success in Revenue Growth, Trade Spend Optimization, and Customer Planning, Pricing, Promotion Optimization, Price Pack, etc
  • Proven track record to get things done in a matrixed organization – including the ability to influence without authority
  • Experience in managing relationships with external data vendors and analytics service providers
  • Strong analytical skills with expertise in Data Interpretation, Visualization, and Reporting
  • Excellent communication and storytelling skills – ability to convert analytical findings into clear business recommendations
  • Experience with analytical tools such as Excel, Power BI, Tableau, or SQL is a plus
  • Leadership qualities to guide teams, foster collaboration, and drive business impact.


C5iis proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of race, color, religion, sex, sexual orientation, age, marital status, disability, gender identity, etc. If you have a disability or special need that requires accommodation, please keep us informed about the same at the hiring stages for us to factor necessary accommodations.

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.

Jobs

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

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

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

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.