Senior Data Analyst

Job Description

The Data Analyst explores historical, real time and future information to deepen understanding of customer attitudes and behaviors. They identify possibilities for a brand and shape the strategy presented to the client.

Senior Data Analyst

Also known as...

Data Analytics

The role in brief...

The Data Analyst explores historical, real time and future information to deepen understanding of customer attitudes and behaviors. They identify possibilities for a brand and shape the strategy presented to the client.

The Senior Data Analyst brings advanced analysis, modelling and performance measurement on projects across the agency. Clear on the purpose of data, how to capture, manipulate, interpret and apply it, they demonstrate the value and impact of this sophisticated science to inform client behaviors and activities. They have the ability to describe, predict and improve business performance. They bridge data and strategy to tell a straightforward and compelling business story.

Working with...

  • Internal: Client Teams; Strategy; Insight Executives; New Business Team, Data Teams across the network, as appropriate, Commercial Producers, Finance Team; HR/Talent Team; Marketing and PR.
  • External: Client contacts, third parties managing data.
  • The Data Analyst may report into the Head of Data.
  • They may have line management responsibility for Junior Data Analysts being accountable for their performance and providing them with professional development opportunities.

Responsible for...

  • Informing and coaching clients to develop a better understanding of the role of data and the inherent possibilities this represents – from optimising incremental behaviours and performance to transforming the future and fortunes of a business.
  • Building innovative and effective approaches to solve client's analytics problems and communicating clear and relevant results and methodologies.
  • Designing experiments and testing hypotheses from which to draw possible approaches and recommendations.
  • Developing data strategy and building measurement framework, KPIs and data architecture.
  • Handling and mining of large, diverse data sets with an ability to work with both structured and unstructured data.
  • Building sophisticated dashboards.
  • Managing large scale data projects.
  • Working with the clients directly they have the experience to determine the right hypothesis to test, to define the right methodologies to query and extract insights and be brilliant in delivery of outcomes and recommendations.
  • Interpreting the analysis to tell a straightforward and compelling business and communicate this effectively to a wide audience with different business interests and skill sets.
  • By identifying trends and patterns they help organisations make better business decisions.
  • Involved in recruitment and selection decisions.
  • Focused on the personal and professional development of their team.

Those who succeed are...

Passionate about analytics and data for off and online digital channels (social channels, website, apps.) Off- line data includes personal information purchase histories, loyalty card data, demographic data and more. They are curious and inquisitive, challenging the data with a passion for understanding and asking why. They blend business insight with commercial relevance. They have mastery in a range of tools and applications:

  • Proficiency in SQL and one or more of the following languages: R, Python, Matlab.
  • Adobe Analytics, Google analytics, Google Data Studio (supermetrics).
  • Social analytical tools like: IBM Watson, Crimson Hexagon, Affinio, Cubeyou, Spredfast Intelligence, Brandwatch.
  • Familiar with other business intelligence tools like Appbot, Quid,
  • Proficiency in Excel, with mastery using the Pivot and Lookup tables, familiarity with VBA.
  •  AdExpress, TGI, Comscore, Omniture.

Where they come from, and where they go…

Data Analysts are very comfortable working with numbers and bring business acumen to the role. They typically study related subjects, such as: Maths and/or Statistics; Finance and/or economics; Computer science; Information management; Business information systems.

Many areas of study and professional experience that can support a data analysis career including analytics, marketing, IT, and customer service.

At the beginning of their career there is a Level 4 Apprenticeship. Which may be an alternative to studying at university.

They may have started an MSc or PhD in a quantitative field as they progress their careers to Data Analyst Director, Head of Data roles.


What is the difference between Data Analytics and Data Analysis?

The main difference between analytics and analysis is a matter of scale, as data analytics is a broader term of which data analysis is a subcomponent.

Data Analysis

Examines, transforms and arranges a given data set in specific ways in order to study its individual parts and extract useful information. The data analyst  collects, analyses, and translates data into information that’s accessible.

Data Analytics

Encompasses the complete management of data. This not only includes analysis, but also data collection, organisation, storage, and all the tools and techniques used.

These terms may be used interchangeably in some agencies.

Last updated 21 January 2022