Client Analytics Lead

About WPP

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. For more information, visit WPP.com.

ABOUT THE ROLE:

The Client Analytics Lead working under the guidance of the Director partners closely with the client and internal stakeholders to develop and deploy analytics for insights, targeting, planning and measurement to enhance the agency products and services for clients. You should have a strong understanding of tools in the media analytics and research space as this role requires hands-on work in analytics. You will also be made familiar with current modelling and technology offerings in the company to be able to curate solutions for relevant project opportunities.

The Client Analytics Lead leads a mid-size team as part of a larger group. Besides data analysis and modelling skills you should have an interest in mentoring and developing team members and ensure deliveries are met. This role requires an ability to manage workflow for the team across multiple brands and deliverables pertaining to measurement frameworks, analytics roadmaps, data governance, analytics delivery, interpretation of results and preparation of reports and presentations to communicate and apply the insights. You are expected to manage periodic client-facing presentations, team development and other stakeholder interactions; and more.

YOUR IMPACT:

Primary responsibilities revolve around design and delivery of analytics powered solutions for insights, targeting, planning and measurement to enhance the agency products and services for client’s media investments:

• Team and work management responsibilities

• Build, manage and mentor a team of analysts

• Manage internal and external client relationships to guide the Analytics engagements

• Manage relationships with clients / be very client facing in approach

• Define and navigate the utilization of the team to optimally deploy resources across the project.

• Guide the team in application of the required analytics relevant to each project.

• Ensure continuous learning and development for the team

• Be informed of various solutions available in the market and evaluate vendors and technologies in the market relevant to delivering econometric, attribution, and experimentation solutions.

• Lead client analytics workstreams with proficiency in O-I-A (observation, insight & action) and manage monthly status reporting, QBRs, wrap-ups, internal updates, etc. Build and drive value in presenting the work done via effective storytelling with the client.

• Technical requirements

• Lead advanced analytic engagements with Client alongside data strategy, planning and measurement teams to understand and translate the strategic vision of the client into clear and actionable briefs for the agency team.

• Creation and execution of end-to-end analytics solutions requiring – data understanding, analysis roadmap, data preparation, analytics, deriving insights and showcase of work done.

• Knowledge of and application experience of prevalent analytics methodologies in data validation, trend analysis, causality approaches (frequenst, Bayesian, etc), various classification algorithms, etc.

• Working knowledge of various analytics and data visualization tools and platforms available in the market.

• Gain mastery of proprietary Choreograph tools and systems primarily focused on analytics related to econometrics, attribution & experimentation covering data preparation, modelling, visualization, etc.

• Knowledge of data pipelines from digital platforms and vendors; expertise in data governance, data quality, QA practices, etc. Ability to interface with various data storage platforms available in the industry.

• Design and management of research projects where applicable (Kantar, Upwave, CINT, DISQO, Dynata etc)

KEY SKILLS:

• Hands-on statistical modeling, especially marketing mix modeling, segmentation, and clustering

• Data wrangling and exploring capabilities, being able to use SQL/Python extract, transform and analyze data

• Data visualization capabilities, being able to create dashboards and visualize data in a digestible format

• Leadership capabilities, coordinate with data team and lead the delivery of the region

• Being able to interpret market test results.

YOUR QUALIFICATIONS:

• Bachelor's or advanced degree in Statistics, Economics, Business, Math, or Sciences is preferred

• Minimum of 4 to 6 years’ experience preferred.

• Experience managing a team.

• Multi-category experience in delivering analytics solutions; work experience in the media/advertising domain is desirable.

• Strong analytics and problem-solving skills.

• Excellent written, oral, and presentation communication abilities.

• Ability to foster collaborative relationships with other cross-functional teams.

• Ability to manage and prioritize competing projects and deliverables.

• Experience with and expertise in with a variety of the following tools and platforms preferred:

• Data Visualization – DOMO, Tableau, PowerBI

• Web Analytics - Google Analytics, Adobe Analytics

• Data warehousing/ web computing solutions

• Advanced Analytics solutioning (attribution analytics, agent-based modelling, Spot Lift, Performance Modelling, frequentist and Bayesian causality algorithms, classification algorithms, data fusion, propensity modelling, audience analytics, etc across client and customer transaction data and structured and unstructured big-data from media platforms)

• Syndicated Measurement: Nielsen, comScore

• Familiarity of data flow in the digital advertising ecosystem and the peculiarities of different digital platforms.

• Ad Effectiveness Research: Kantar Millward Brown, Upwave, CINT, Dynata, DISQO

• Expertise in SQL, R, Python and desirable exposure to different low-code/ no-code data and analytics platforms available

• Latest AI-based analytics solutions/ platforms available in the industry

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