Data Analytics & Business Intelligence Senior Associate

About the role

The role investigates measurement techniques to strengthen organizational prediction and turn complex data into actionable insights for clients. You will design and execute analyses that clarify how media performance links to business outcomes, ensuring findings are robust and reproducible. A core part of the work involves building and maintaining data structures that integrate fragmented sources into a coherent view of media impact. You will partner with media and business stakeholders to translate ambiguous questions into analytical plans that address real client needs. The position requires you to communicate technical results to non-technical audiences in a clear, concise, and persuasive manner. You will contribute to a data-driven culture within WPP Media by creating dashboards, reports, and frameworks that support ongoing experimentation. This role emphasizes curiosity, rigor, and ownership so that insights move from retrospective reporting to forward-looking guidance. You will help define best practices for measurement and evaluation across teams, shaping how data informs strategic media decisions.

Key facts

What you'll do

Reliable insights and measurable business outcomes for clients emerge from data integration, transformation, and analysis across multiple sources.

You will construct and maintain databases, data tables, and analytical datasets that serve as the foundation for media measurement and performance evaluation.

Clients and internal audiences gain data in formats that guide media decisions, requiring you to structure outputs for clarity, scalability, and repeatability.

Core task performance requires demonstrating advanced knowledge of Python, SQL, and relational/non-relational databases, including data integration, transformation, and automation.

You will apply statistical analysis, experimentation, measurement frameworks, and basic machine learning techniques to support objective evaluation and prediction in media contexts.

Familiarity with digital marketing analytics and measurement platforms, including Google Analytics 4, Google Tag Manager, and media data ecosystems, will be used to analyze performance and troubleshoot data issues.

You will translate complex data for stakeholders through clear narratives, visualizations, and presentations, ensuring that findings are actionable for media planning and buying.

The role involves working with platforms such as WPP Open and Open Intelligence to connect media, data, and partnerships, enabling data-driven decisions at scale.

You will collaborate with cross-functional teams to define metrics, validate data quality, and align analyses with business objectives across the WPP media collective.

Expect to document methodologies, challenge assumptions, and iteratively refine analyses to improve accuracy, transparency, and impact over time.

Requirements

Foundational knowledge for the role comes from a bachelor's degree or equivalent in a quantitative or business-oriented field.

Core task performance requires demonstrating advanced knowledge of Python, SQL, and relational/non-relational databases, including data integration, transformation, and automation.

You must show the ability to work with statistical analysis, experimentation, measurement frameworks, and basic machine learning techniques to support objective evaluation and prediction.

Effective analysis within common media environments depends on familiarity with digital marketing analytics and measurement platforms, including Google Analytics 4, Google Tag Manager, and media data ecosystems.

Clear translation of complex data for stakeholders depends on strong analytical, problem-solving, and communication skills.

You must meet these hard requirements to ensure readiness for the responsibilities of the role.

The position is open to candidates who hold a Bachelor's degree or equivalent and can demonstrate practical competence in the required tools and methods.

Experience working with data in media, marketing, or related environments is expected, along with a track record of using data to inform decisions.

Strong written and verbal communication skills are essential for explaining analytical approaches, results, and implications to both technical and non-technical audiences.

You should be comfortable working in a hybrid environment, collaborating with distributed teams and adapting to evolving priorities in a global media network.

Practical notes

Accommodations can be discussed during the interview process if needed.

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Work in this role often happens within data-driven media environments focused on creative personalization at scale.

Professionals commonly use platforms such as WPP Open and Open Intelligence to connect media, data, and partnerships.

Strong analytical and communication skills are essential for turning complex data into client actions.

The position values growth, trust, and collaborative problem-solving within a global network.

Questions to ask

Useful questions for the interview: what a typical week looks like, how work is assigned, what tools the team uses, and how feedback works.

Asking how the role has changed recently and what the team wishes it had known when joining is also reasonable.

Questions about the manager's priorities are especially valued.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead.

Many professionals specialize in machine learning, analytics, or infrastructure.

Cross-functional work with product and engineering teams becomes more important at senior levels.

The field changes quickly, so continuous learning is part of the job.

Professionals who can translate numbers into decisions tend to advance fastest.