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Data Analyst ref:H225
Posted 10 days 15 hours ago by Tasman
Permanent
Full Time
I.T. & Communications Jobs
London, United Kingdom
Job Description
Role Summary We are hiring a Data Analyst to:
For data products, the Data Analysts collaborate closely with Analytics Engineers and Data Engineers to design and build the required components. They create Product Briefs that describe requirements in detail to provide a central point of design and discussion. They also take responsibility for the design and build of informative dashboards.
For analysis, Data Analysts will work more autonomously to deep dive into the data and generate robust insights. They collaborate with Analytics Engineers to build analysis-ready datasets and with other Data Analysts to bounce ideas and review insights. Throughout the analysis process, they work closely with client stakeholders to iterate quickly through findings and hone in on the high value outcomes.
Business Analysis & Data Strategy At the core of Tasman's delivery approach is a focus on business value and solutions that target specific business needs. Our Data Analysts work closely with clients to understand their business model and challenges, allowing us to shape solutions that precisely fit their requirements. Clear communication of these requirements to both the Tasman team and the client is crucial for successful delivery.
The scope of business analysis work varies with solution complexity. For simpler cases, we deliver quick results through brief summaries and close collaboration with our data platform team. More complex situations require comprehensive product briefs to align all stakeholders-both client and Tasman team members-on the solution's direction. An exceptional Data Analyst instinctively knows which approach best suits each business situation.
In summary, you will:
We use a common approach to data models that we deploy across all clients. That means analysis is built on the same data platform and can be reused and tailored to produce rapid results, as well as deep analysis. The cumulative effect of these standardisation efforts is that we shorten the time-to-value with each new client we work with.
For bigger or longer-term questions, exploratory data analysis is a key part of how we approach client problems and realise business value. We use a scientific approach to uncover key insights and relationships between key elements of the business. Using a combination of simple analytical approaches, sophisticated visualisations, and statistical modelling we unpick the true signals in the data and discard the spurious noise.
In summary, you will:
Self-serve analytics can get complicated very quickly, so we have tried-and-tested approaches to developing multi-layered reporting systems that are tailored to each client. Our Data Analysts carefully design the information architecture and data visualisations to create dashboards that are easy to understand and embedded within business processes. Developing simple navigation pathways between visualisation tools and datasets unlocks the full power of self-serve analytics, enabling our clients to make more data-informed decisions.
By combining technical expertise with a strong understanding of storytelling, our Data Analysts create data visualisations that not only inform but also inspire. We believe that data, when presented effectively, can transform businesses.
In summary, you will:
In summary, you will:
- Work closely with clients to understand their specific needs and challenges.
- Transform complex business requirements into clear data-driven solutions.
- Design and develop user friendly data products to empower clients with self-serve analytics.
- Utilise fundamental and advanced analytical techniques to uncover valuable insights and inform strategic decision-making.
- Collaborate with the Tasman team to build and maintain a robust data platform that supports business growth for our clients
For data products, the Data Analysts collaborate closely with Analytics Engineers and Data Engineers to design and build the required components. They create Product Briefs that describe requirements in detail to provide a central point of design and discussion. They also take responsibility for the design and build of informative dashboards.
For analysis, Data Analysts will work more autonomously to deep dive into the data and generate robust insights. They collaborate with Analytics Engineers to build analysis-ready datasets and with other Data Analysts to bounce ideas and review insights. Throughout the analysis process, they work closely with client stakeholders to iterate quickly through findings and hone in on the high value outcomes.
Business Analysis & Data Strategy At the core of Tasman's delivery approach is a focus on business value and solutions that target specific business needs. Our Data Analysts work closely with clients to understand their business model and challenges, allowing us to shape solutions that precisely fit their requirements. Clear communication of these requirements to both the Tasman team and the client is crucial for successful delivery.
The scope of business analysis work varies with solution complexity. For simpler cases, we deliver quick results through brief summaries and close collaboration with our data platform team. More complex situations require comprehensive product briefs to align all stakeholders-both client and Tasman team members-on the solution's direction. An exceptional Data Analyst instinctively knows which approach best suits each business situation.
In summary, you will:
- work directly with clients to refine scope of stories, using probing questions and discovery techniques to uncover underlying business needs and clarify true pain points, especially when initial requests are vague or ambiguous, ensuring deliverables (dashboards, analyses, or other data products) provide tangible business value to stakeholders
- transform abstract business problems into concrete, measurable data requirements by breaking down complex request into actionable components, then create comprehensive documentation that serves as a single source of truth for both technical teams and business stakeholders
- describe the scope and requirements in detailed written form, working closely with analytics engineers to elaborate on product briefs and ensure complex requirements are fully described to avoid potential pitfalls
- prioritise requirements based on business value, effort, and strategic alignment to maximise impact within resource constraints, recognising inter-dependencies between data related decisions and broader business goals with an understanding of long term implications
- build trusted advisor relationships with stakeholders by demonstrating deep understanding of their business context and proactively suggesting data solutions to emerging challenges, and showing how data decisions connect to their strategic roadmaps
We use a common approach to data models that we deploy across all clients. That means analysis is built on the same data platform and can be reused and tailored to produce rapid results, as well as deep analysis. The cumulative effect of these standardisation efforts is that we shorten the time-to-value with each new client we work with.
For bigger or longer-term questions, exploratory data analysis is a key part of how we approach client problems and realise business value. We use a scientific approach to uncover key insights and relationships between key elements of the business. Using a combination of simple analytical approaches, sophisticated visualisations, and statistical modelling we unpick the true signals in the data and discard the spurious noise.
In summary, you will:
- have a comprehensive understanding of the data that is currently available in the data warehouse in various states of analytics-readiness
- be able to use the available data in creative ways to answer business questions quickly but robustly
- leverage understanding of the client business and similar industries to zoom in on most useful insight quickly
- use a structured analysis process to investigate a business problem and provide clear data-driven evidence for recommended solutions
- prepare reports to communicate results of analysis back to stakeholders in a format that is appropriate to the audience and the analysis. This will often require presenting the results back to stakeholders
- be able to use inferential statistical tests to validate hypothesis, understanding when to use tests and how results are communicated to stakeholders.
Self-serve analytics can get complicated very quickly, so we have tried-and-tested approaches to developing multi-layered reporting systems that are tailored to each client. Our Data Analysts carefully design the information architecture and data visualisations to create dashboards that are easy to understand and embedded within business processes. Developing simple navigation pathways between visualisation tools and datasets unlocks the full power of self-serve analytics, enabling our clients to make more data-informed decisions.
By combining technical expertise with a strong understanding of storytelling, our Data Analysts create data visualisations that not only inform but also inspire. We believe that data, when presented effectively, can transform businesses.
In summary, you will:
- design dashboards that communicate targeted information to stakeholders in a digestible format. The designs are specific to the use-case and take account of the information hierarchy and the stakeholders involved
- build dashboards in a variety of BI platforms such as Looker and Omni, owning the semantic layer to develop explore designs that facilitate self serve analysis
- deliver engaging presentations that effectively communicate key insights to diverse stakeholder groups, using data storytelling techniques to craft compelling narratives that resonate with the audience and drive understanding
- works with Analytics Engineers to QA data models and dashboards to ensure data is accurate and reliable.
In summary, you will:
- use AI tools to accelerate code development, debugging and documentation for your work
- automate repetitive tasks such as report generation, data quality checks, and dashboard updates using AI-assisted workflows
- generate initial drafts of product briefs, analysis reports, and stakeholder communications using AI, then refine with domain expertise and client knowledge
- maintain awareness of AI limitations, biases, and hallucinations, especially when working with client-sensitive or business-critical analyses
- document when and how AI tools were used in analysis to maintain transparency with clients and team members
Tasman
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