Senior Business Intelligence Analyst (Contract)

M3
Abingdon
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Business Intelligence Analyst / Data Manager

Senior Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst | Kent and Medway Mental Health NHS Trust

Senior Business Intelligence Analyst (Contract)

M3 Abingdon-On-Thames, England, United Kingdom

About the Business Division:
This role sits within Doctors.net.uk, a subsidiary of M3 Inc. Doctors.net.uk is the UK's largest professional network of doctors; a closed community used by over 50,000 doctors daily and with a total membership of over 245,000. Products range from a trusted email communications platform to robust news and educational web pages along with our world-class sponsored pharmaceutical content and doctors’ own user-generated content. Our mission is to continually improve these offerings as well as identifying new ways to support our community of doctors throughout their careers.

Job Description:
As an M3 EU Senior Business Intelligence Analyst (Contract), you will be responsible for delivering and maintaining innovative, market-leading digital data dashboards, reports, and insights. You will work closely with commercial and operational teams to gather and distil relevant customer insights to create compelling data stories that meet the needs of clients and support our commercial objectives, as well as delivering on our short- and long-term business strategy.

In this role, you will work closely with the Product and Data Engineering Teams to understand requirements and liaise with the data engineering team on required improvements before creating and delivering best-in-class reporting and insights. You’ll have the opportunity to bring a passion for innovative visual and verbal data narratives to a well-established business in need of an organised, productive data analyst.

Essential Duties And Responsibilities:

  • Client Dashboard and Report Creation and Maintenance – including QA and data integrity
  • Client KPI model refinement – regular review of our client KPI model and forecasting process
  • Internal KPI setting and results analysis for Product and Community teams
  • Data Analysis – regularly review data outputs to identify actionable insights that can be used to improve the business
  • Verbal Communication – requirement gathering, cross-functional collaboration to understand the needs of the business
  • Visual Communication - storytelling through data visualisation and data narratives

Qualifications:

  • Data Toolkit - Applied knowledge of data & analytics tools and approaches across all data lifecycle stages. Data visualisation tools such as Tableau, Power BI, Qlik. Languages including SQL, Python, frameworks such as DBT
  • Data Visualisation - Keen interest in visualisations and storytelling through data
  • Expert communicator - Ability to explain complex concepts in simple terms
  • Compliance - Experience with data compliance (GDPR and regulated industries)
  • Customer-centric with a pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail. Deadline-oriented, detailed, a self-starter
  • Entrepreneurial - a curiosity about business advancement and a strategy thought-partner
  • Experience – 5+ years’ experience

Additional Information:

Benefits:

  • 25 days annual leave
  • Participation in a company bonus scheme linked to personal and company performance
  • Group Life Cover 4x salary
  • Pension 4%/4% employee/employer contributions
  • Vitality medical after probation
  • Staff discount scheme
  • Discounted gym membership

About M3 EU:
M3 EU is at the forefront of healthcare innovation, offering digital solutions across healthcare, life sciences, pharmaceuticals, and more. Since our inception in 2000, we’ve seen remarkable growth, fuelled by our mission to utilize the internet for a healthier world and more efficient healthcare systems. Our success is anchored in our trusted digital platforms that engage physician communities globally, facilitating impactful medical education, precise job placement, and insightful market research. M3 EU prides itself on a dynamic and innovative work environment where every team member contributes to global health advancements.

Joining M3 EU means being part of a dedicated team striving to make a significant difference in healthcare. We provide a unique opportunity for you to be at the cutting edge of healthcare innovation, shaping the future in a meaningful career. Embrace the chance to drive change with M3 EU.

Seniority level

  • Mid-Senior level

Employment type

  • Full-time

Job function

  • Information Services


#J-18808-Ljbffr

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.