Principal Data Analyst
Job in
New York City, Richmond County, New York, USA
Listed on 2026-02-02
Listing for:
WPP PLC
Full Time
position Listed on 2026-02-02
Job specializations:
-
IT/Tech
Data Engineer, Data Analyst, Data Science Manager, Data Scientist
Job Description & How to Apply Below
Who we are & what we do:
Gain Theory is a leading global marketing effectiveness and foresight consultancy. We combine quality data, proprietary technology, and advanced analytics to give our clients the confidence to make better informed investment decisions that drive growth.
Growth is the defining characteristic of successful organizations, and Gain Theory's vision is to accelerate growth for ambitious brands. We define ambitious brands as those that generate earnings/profits above the industry average. We deliver:
* Data strategy, harmonization, and visualization.
* Advanced analytics and modeling, including MMM, attribution and unified measurement, testing, segmentation, behavioral sciences, choice analytics, simulation, war gaming, and forecasting.
* High-touch consultancy that includes bespoke roadmaps, training and education, industry benchmarking, and activation planning.
At Gain Theory, we love accelerating growth for ambitious brands and people. As a Gain Theorist, you will need to demonstrate behaviors that support our values.
Our values are:
Be Curious, Be Positive, Act with Consideration, and Make it Better. You can read more about our values here:
What you'll do:
As a Principal Data Analyst, you will join the Gain Theory Data Practice and be embedded within one of our client-focused squads. Working closely with your manager, you'll collaborate on some of the world's top brands, gaining hands-on experience with diverse data sources-including media, client-specific, Gain Theory proprietary, sales, and more.
In this role, you'll be part of a team that processes and organizes data in preparation for modeling. You'll face exciting challenges and have opportunities to drive innovation and automation across workflows.
As a Principal Data Analyst, you will apply data processing techniques such as SQL, ETL and Python alongside our internal automation tools, to manage, clean, and transform data through efficient pipelines. You'll also run rigorous data quality assurance processes-ensuring data integrity, which is the foundation of all our work. Additionally, you'll collaborate with the Data Manager to coordinate with client and agency partners, maintaining the continuous flow of data from key sources.
Beyond your squad, you'll engage with the wider Gain Theory data community, including the Data Centre of Excellence (DCOE), to share best practices and both provide and receive support. The Principal Data Analyst will also mentor and support junior analysts on their projects, helping them learn processes, best practices, and specific tools used by Gain Theory.
At Gain Theory, our teams combine cutting-edge data engineering, advanced analytics, unified measurement solutions, and enterprise-scale platforms to build products that will shape the next decade of faster, smarter, data-informed decision-making. We are committed to ensuring consumer privacy, safeguarding client confidentiality, driving brand growth, and delivering exceptional user experiences.
Key Responsibilities:
Data Management & Analysis:
Manage data extraction, manipulation and validation.
* Manage data extraction, manipulation, validation, and interrogation using SQL, Python, and other relevant tools.
* Build data QA insights relevant to the project
* Ensure that all data is systematically checked and passes all QA steps
Data Architecture:
Execute and update data pipelines
* Building and maintaining data ingestion and transformation pipelines using all the tools that Gain Theory has at your disposal
* Build data ingestion and transformation pipelines using available tools, including Python scripting for data processing and automation.
* Working with fellow data analysts to building scalable solutions using ETL/ELT pipelines
Research & Development :
Support wider improvements in data
* Propose better approaches to help improve internal procedures including new methodology, etc.
* Share techniques and ideas with the wider data community
Meetings:
Organisation and participation in internal meetings
* Initiate and engage with internal project meetings, ensure there is an agenda
* Ensure that project meeting action points are…
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