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Senior Data Analyst – European Merchandising Analytics

circlek10,995 open roles

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Support Office Oslo
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Your applicationOpen nowSenior Data Analyst – European Merchandising Analyticscirclek · Support Office Oslo

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. circlek postings stay open a median of 20 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted today

circlek median: 20 days open

The posting

Job Description

Senior Data Analyst – European Merchandising Analytics

Department: Data & Analytics Location: Oslo, Norway Type: Fixed-term 2-year contract / parental leave backfill

We’re seeking an experienced and commercially minded Senior Data Analyst to join our European Data & Analytics team and support our Merchandising organization.

As a Senior Data Analyst, you will be a trusted analytics partner to European Merchandising and Category teams, helping translate complex business questions into actionable insights and scalable analytical solutions. You will work across multiple categories, markets and stakeholders, using transactional, financial, customer and operational data to identify opportunities and improve business performance.

This role requires a strong combination of analytical capability, commercial understanding and stakeholder management. You should be comfortable independently leading analytical work from problem definition through recommendation, while collaborating with analysts, data scientists, technology teams and business stakeholders across Europe.

You will join an experienced international analytics team and have the opportunity to contribute to the continued development of Circle K’s merchandising analytics capabilities.

RESPONSIBILITIES / ACCOUNTABILITIES

  • Partner with European Merchandising, Category and other business teams to understand priorities, define business questions and translate them into analytical requirements and measurable KPIs.
  • Apply advanced analytical techniques where appropriate, including forecasting, clustering, regression, hypothesis testing, causal impact analysis and other statistical methods.
  • Act as a data-driven thought partner to business stakeholders, providing insights and constructively challenging assumptions and priorities based on data.
  • Evaluate category and commercial performance using transactional, financial, customer and operational data, identifying trends, opportunities and areas requiring action.
  • Independently lead analytics projects from problem definition and data exploration through analysis, recommendation and stakeholder communication.
  • Develop actionable insights related to areas such as category performance, assortment, pricing, promotions, customer behavior and other merchandising initiatives.
  • Design and evaluate business experiments and pilots, including test design, measurement methodology, performance evaluation and interpretation of results.
  • Develop and improve scalable dashboards, analytical tools and reporting solutions that enable business teams to monitor performance and make better decisions.
  • Collaborate with Data Engineering, Technology and other Data & Analytics teams to improve data quality, analytical datasets and reusable analytics capabilities.
  • Identify opportunities to automate recurring analytical processes and improve the efficiency and scalability of analytics delivery.
  • Translate complex analytical findings into clear, concise and actionable recommendations for both technical and non-technical audiences.
  • Present insights and recommendations to stakeholders and contribute to decision-making across European Merchandising.
  • Contribute to a collaborative analytics community by sharing knowledge, methodologies and best practices across teams and geographies.
  • Perform other related duties as assigned.
  • Experience using AI agents or AI coding tools to automate analysis work, or building simple AI tools for business users, is a plus.

QUALIFICATIONS & EXPERIENCE

  • A higher degree in an analytical discipline such as Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Finance or a related field.
  • 3+ years of experience in analytics, data science, business intelligence or a related analytical role.
  • Strong analytical and problem-solving skills, with demonstrated experience turning complex data into actionable business recommendations.
  • Hands-on experience applying analytical methods such as forecasting, regression, hypothesis testing, clustering and A/B tests, including checking model accuracy on past data and showing the uncertainty in the results.
  • Experience in retail, merchandising, category management, FMCG, e-commerce or other commercial analytics environments. Experience analyzing pricing, promotions, assortment, category performance or customer behavior.
  • Experience working with large datasets using SQL and analytical/programming tools such as Python, PySpark. Experience with Databricks, Azure or other cloud-based analytics platforms is a plus.
  • Experience developing dashboards and analytical solutions using tools such as Power BI or similar BI platforms.
  • Ability to independently structure ambiguous business problems and drive analytical work from initial question through delivery.
  • Excellent communication skills in English, both written and verbal, with the ability to explain complex analytical concepts to non-technical audiences.
  • Strong stakeholder-management skills and the ability to collaborate effectively across functions, countries and levels of seniority.
  • Ability to manage multiple priorities and communicate timelines, dependencies and risks clearly.

PERSONAL QUALITIES

  • You think analytically, commercially and pragmatically.
  • You are curious and enjoy understanding both the business problem and the data behind it.
  • You are comfortable with ambiguity and can bring structure to complex problems.
  • You take ownership and can independently drive work through to completion.
  • You build strong relationships with stakeholders and are comfortable constructively challenging assumptions using data.
  • You can translate complex information into clear, compelling and actionable insights.
  • You value collaboration and actively share knowledge and best practices with colleagues.
  • You are adaptable and interested in continuously developing your business and technical capabilities.
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