Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Business Intelligence Data Analyst

Foresters Financial
Bromley
3 months ago
Applications closed

Related Jobs

View all jobs

Business Intelligence/Data Analyst

Data Analyst, Business Intelligence Data Analyst

Data Analyst, Business Intelligence Data Analyst

Data Analyst, Business Intelligence Data Analyst

Lead Data Analyst

Senior Data Engineer

As our Business Intelligence Data Analyst for a 12 month Fixed Term Project you will be responsible for designing and developing reports and dashboards using Power BI to support customer analysis, sales reporting, and product analysis for clients across all departments. 

Reporting to the Business Solutions and Support Manager, you will be part of a team championing the effective use of BI throughout the organisation. This also involves preparing communications and presentations, assisting the business in obtaining solutions to complex problems and communicating issues adversely impacting the business to management.

Your day to day will include:

  • Developing a thorough understanding of business objectives and issues, interpret business needs into data and analytical requirements, and deliver valuable insights to internal customers to support operational needs and strategic planning
  • Supporting the planning, identification, development and implementation of design and/or changes to key reports and ad hoc requests
  • Designing and developing reports and dashboards using Power BI to support customer analysis, sales reporting, and product analysis for clients across all Foresters stakeholders
  • Working collaboratively to drive business value out of the Data Warehouse and other data sources
  • Leading, collecting and analysing business requirements for small to medium sized development efforts (both short and long-term solutions). Recommending and delivering solutions.
  • Anticipating future data needs and working with other teams to ensure we have access to required data to support business needs including identification and specification of changes to the Data Warehouse
  • Promoting and fostering the adoption of business intelligence as a driver for effective decision-making
  • Ensuring an extremely high level of accuracy and quality of all management reports
  • Raising project risks, issues and dependencies to appropriate business owners and PMO offering mitigating actions and taking ownership of individual items where appropriate.


What we require

  • Experience is an Business Intelligence/analytical and /or data  role
  • Strong experience in Power BI would be desirable
  • Extensive experience using SQL
  • Advanced MS Excel
  • Strong written and verbal communication skills with an ability to convey technical information to non technical audiences
  • Ability to work autonomously and self motivate
  • Excellent organisational and project management skills to meet deadlines and handle changing priorities
  • Financial Services, Insurance and/or Savings & Investments experience beneficial.


What we offer you

  • Annual salary up to £55,000
  • 25 days holiday plus bank holidays rising to 28 days.
  • Life Assurance (4x pensionable earnings)
  • Contributory Pension scheme (company contribute up to 10%)
  • Employee Assistance Programme

Working hours are 40 hours a week Monday to Friday. Start times can vary from 7.30am to 9.30am. After a successful training period there is flexibility to work from home up to 3 days a week.

INDAD

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.