Senior Data Analyst

Kennedys
Manchester
4 days ago
Create job alert
Job Overview

This position is for a senior data analyst with strong experience in insurance claims and claims related analysis. The role requires expert SQL skills, solid Power BI capability and the ability to produce clear visual analytical outputs. The analyst will work across internal product analytics and external client-facing insights that support business decisions, claims strategy and offer strategy.


Team

Kennedys IT team delivers a responsive, effective, and timely IT support service to the firm's employees and clients. They devise and implement operational processes and procedures in order to provide reliable and available IT systems to the firm.


Key Responsibilities

  • Serve as a project resource on Kennedys IT projects as required, contributing technical expertise and ensuring alignment with project goals.
  • Deliver internal analytics that help the business understand software usage, product performance and adoption patterns.
  • Build external client‑facing dashboards and reports that explain claims trends, operational performance, outcomes and strategic opportunities.
  • Work closely with product, engineering and client teams to translate analytical findings into clear recommendations.
  • Support the development of analytical frameworks and enable actionable metrics that help clients evaluate claims strategy and operational effectiveness.
  • Clean, prepare and validate large datasets drawn from claims systems, product telemetry and operational sources.
  • Create Power BI dashboards that present complex information in a clear and actionable format.
  • Carry out deep dive analysis to understand drivers of claim cost, duration, liability and settlement patterns.
  • Develop SQL queries and data models that ensure reliable and repeatable analytical outputs.
  • Present findings to senior internal stakeholders and client decision makers using strong narrative and visual storytelling.
  • Contribute to ongoing improvement of data quality, definitions and governance.

Required Experience

  • Advanced SQL skills with the ability to work with complex relational datasets.
  • Strong Power BI experience including DAX, modelling and report design.
  • Proven ability to create visually clear, user‑centric, analytical and understandable presentations.
  • Background in insurance claims, financial services analytics or related decision support fields.
  • Experience working with senior stakeholders and non‑technical audiences.
  • Strong problem‑solving and analytical thinking.
  • Ability to work independently, specify requirements for junior colleagues and manage multiple analysis streams.
  • Demonstrable experience with Tableau is an advantage.
  • Experience of enabling best data‑quality management practices, and introduction of data governance processes is an advantage.
  • Curiosity and a desire to understand how claims processes and claim outcomes work.
  • Ability to communicate complex ideas simply.
  • High attention to detail and accuracy.
  • Comfortable collaborating across technical and non‑technical teams.

*Where a level of experience is indicated, this is a guideline only and represents the amount of time we would usually expect a candidate to accumulate the requisite level of experience. This does not preclude applications from candidates with more or less experience.


Please let us know if you require any additional support or adjustments to be made in order to submit your application to Kennedys.


Documents

  • PDF Senior Data Analyst March 2026.pdf (64.43 KB)

Equal Opportunities Employer

Kennedys is an equal opportunities employer and is committed to ensuring our recruitment processes are as inclusive as possible. We expect all employees to be aware of and comply with all relevant policies and procedures within their jurisdiction, including those relating to Information Security, Data Protection and Quality Management, refer any breach promptly to Risk & Compliance and to complete all mandatory training when requested.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst - Marketing

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.