At a Glance
- Tasks: Transform complex data into actionable insights and support strategic decision-making.
- Company: Leading international Manufacturing & Retail Company with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Fast-paced environment with excellent career advancement opportunities.
- Why this job: Join a dynamic team driving digital transformation and AI adoption in a high-growth environment.
- Qualifications: Experience in data analysis, strong Power BI skills, and a passion for eCommerce analytics.
The predicted salary is between 50000 - 65000 £ per year.
Overview
This leading international Manufacturing & Retail Company is seeking a commercially focused and technically capable Data Scientist to join their Finance team to support a high growth phase into new markets.
The role will support data‑driven decision making across the entire organisation – including Finance, Merchandising, Creative, Licensing, Sales, Supply Chain, e Commerce, and Operations – and help drive commercial decision‑making across retail and digital channels.
Responsibilities include transforming complex business data into actionable insights, building reporting frameworks, identifying trends and opportunities, and supporting leadership teams with strategic analysis and forecasting, while driving the company’s adoption of AI technologies, automation, and modern analytics tools.
Key Responsibilities
- Analyse large and complex datasets across multiple platforms to identify trends, risks, opportunities, and operational improvements.
- Develop and maintain dashboards, KPIs, and reporting suites using Power BI.
- Support the Finance team with forecasting, budgeting, margin analysis, profitability reporting, and commercial insights.
- Partner with Merchandising, Sales, Licensing, Creative, Supply Chain and Operations teams to provide analytical support and performance reporting.
- Build predictive models and analytical tools to support strategic decision‑making and business planning.
- Drive the adoption of AI and automation solutions across the business to improve efficiency and insight generation.
- Work with ERP and operational systems, including D365 Business Central, to extract, validate, and analyse data.
- Improve data quality, governance, consistency, and reporting accuracy across departments to ensure one version of the truth.
- Develop and maintain data pipelines and automated reporting processes where appropriate.
- Present findings and recommendations clearly to senior leadership and operational stakeholders.
- Support ongoing digital transformation initiatives across the business.
- Ensure analytical work follows best practices around governance, security, and ethical AI usage.
- Monitor and analyse e Commerce and marketplace KPIs including conversion rate, click‑through rate (CTR), ACOS, TACOS, Buy Box performance, average selling price (ASP), keyword rankings, and inventory health metrics.
- Support e Commerce and marketplace advertising analysis, including Amazon Sponsored Ads performance, ROAS optimisation, campaign analysis, and budget efficiency reporting.
- Support data‑driven optimisation of e Commerce product listings, keywords, digital content, and marketplace visibility to improve discoverability, conversion and sales performance.
- Conduct competitor, pricing and market analysis to identify trends, opportunities and risks across e Commerce and retail channels.
- Apply predictive analytics and trend analysis to support demand forecasting, inventory planning, and commercial decision‑making.
- Support testing and experimentation across pricing, advertising, promotions and digital content strategies, using analytical insight to measure performance and recommend improvements.
- Work closely with merchandising, e Commerce, licensing and marketing teams to provide commercially focused analytics and actionable insight.
- Profile
Essential Qualifications
- Previous experience within a Data Scientist, Data Analyst, Business Intelligence or Analytics role.
- Strong analytical and problem‑solving skills with commercial awareness.
- Advanced Power BI capability, including dashboard creation, DAX, data modelling and visualisation.
- Strong experience using SQL for querying and manipulating datasets.
- Experience using AI tools, large language models (LLMs) and automation technologies to support analytics, reporting and business insight generation.
- Experience working with ERP systems, preferably Microsoft Dynamics 365 Business Central (BC) and/or Syspro.
- Understanding of AI, machine learning, automation tools and modern analytics techniques.
- Ability to interpret complex datasets and communicate findings clearly to non‑technical stakeholders.
- Excellent communication and stakeholder management skills.
- Highly organised with the ability to manage multiple priorities in a fast‑paced environment.
- Experience working with e Commerce and marketplace analytics, preferably Amazon Seller Central and Amazon Advertising platforms.
- Understanding of e Commerce performance metrics including ROAS, ACOS, TACOS, conversion rate optimisation, keyword ranking and digital traffic analysis.
- Experience translating commercial and marketplace data into actionable business insight.
Desirable Qualifications
- Experience within a consumer products, retail, licensing, apparel, manufacturing or distribution environment.
- Experience with forecasting, demand planning or supply chain analytics.
- Experience developing AI‑enabled business solutions or workflow automation.
- Understanding of financial reporting and commercial finance concepts.
- Degree qualified in Data Science, Computer Science, Mathematics, Statistics, Economics or a related quantitative discipline.
- Experience with Amazon marketplace optimisation tools such as Helium 10.
- Experience using social listening and consumer insight platforms such as Meltwater.
- Experience within licensed apparel, consumer products, retail, e Commerce or marketplace‑driven businesses.
- #J-18808-Ljbffr
Data Scientist - Ecommerce, Marketing & Commercial Operations employer: Michael Page
At Michael Page, we pride ourselves on being an excellent employer that champions community impact through our Social Value Lead role. Our supportive work culture fosters collaboration and innovation, providing employees with ample opportunities for professional growth while making a meaningful difference in the property industry. Located in a vibrant area, we offer competitive salaries and a commitment to employee well-being, ensuring that you thrive both personally and professionally.
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We think this is how you could land Data Scientist - Ecommerce, Marketing & Commercial Operations
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We think you need these skills to ace Data Scientist - Ecommerce, Marketing & Commercial Operations
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Michael Page. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Michael Page
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
