At a Glance
- Tasks: Support data analysis, reporting, and dashboard development in a fast-paced digital environment.
- Company: Join CJ Affiliate, a leader in Global Affiliate Marketing within Publicis Groupe.
- Benefits: Gain hands-on experience with cutting-edge tools and technologies while developing your career.
- Other info: Collaborative team culture with opportunities for growth and exposure to AI technologies.
- Why this job: Make an impact by analysing data and driving insights for innovative marketing solutions.
- Qualifications: 0-2 years in analytics, experience with SQL and Python, and a passion for learning.
The predicted salary is between 28000 - 35000 Β£ per year.
Company Description: As part of Publicis Groupe, CJ Affiliate is the leader in Global Affiliate Marketing. We take pride in our innovative technology, comprehensive data solutions and our people. We equip our teams with the tools, training and career development opportunities to provide cutting edge solutions, strategies and support that deliver high quality results for our clients. We work in an energetic, results-oriented, collaborative, team environment that recognises exceptional performance. As we evolve and grow as a business, so do you.
Overview: Junior Data Science and Marketing Analyst. At CJ, the Junior Data Science and Marketing Analyst supports reporting, analytics, and data-driven decision making across internal teams and client-facing initiatives. This role focuses on data analysis, reporting, dashboard development, and investigating business questions within a fast-paced digital advertising environment.
You will work alongside analysts, data scientists, account teams, and business stakeholders to help deliver reporting, analyse performance data, support measurement initiatives, and build scalable analytics solutions. You will also leverage modern AI tools and coding assistants to improve efficiency, automate repetitive tasks, and accelerate analytics workflows.
What You Will Do:
- Support reporting, analytics, and data requests across internal teams and client-facing initiatives.
- Analyse e-commerce, digital advertising, and performance marketing data to identify trends, opportunities, and business insights.
- Build and maintain Tableau dashboards, recurring reports, and self-service reporting solutions.
- Write SQL queries and utilise Python to support data analysis, validation, automation, and reporting workflows.
- Assist with data investigations, troubleshooting, and quality assurance efforts to ensure reporting accuracy.
- Partner with analysts, account teams, and cross-functional stakeholders to deliver timely and accurate analytics solutions.
- Leverage AI tools, coding assistants, and automation technologies to improve productivity and streamline workflows.
- Learn and apply measurement methodologies used across digital marketing, including campaign performance analysis, attribution, and incrementality concepts.
- Document processes, reporting logic, and analytics workflows to support operational consistency.
What We Look For:
- 0β2 years of experience in analytics, data science, business intelligence, marketing analytics, or a related field.
- Experience writing SQL queries to analyse and manipulate data.
- Experience with Python for data analysis, automation, or reporting.
- Familiarity with Tableau, Power BI, or similar business intelligence tools.
- Strong analytical and problem-solving skills with attention to detail.
- Ability to communicate findings clearly to both technical and non-technical audiences.
- Curiosity and willingness to learn new technologies, analytics methodologies, and AI-enabled workflows.
- Strong organisational skills and ability to manage multiple priorities in a fast-paced environment.
Preferred:
- Experience with Databricks, Spark, or cloud-based analytics platforms.
- Exposure to digital advertising, e-commerce, affiliate marketing, or performance marketing concepts.
- Familiarity with Python libraries such as Pandas, NumPy, or PySpark.
- Experience using AI coding assistants such as GitHub Copilot, Claude Code, Codex, Cursor, or similar tools.
- Exposure to marketing analytics concepts such as attribution, campaign measurement, incrementality testing, or marketing mix modeling (MMM).
- Internship, coursework, personal projects, or professional experience involving data analysis, reporting, or dashboard development.