Senior Business Development Manager - Business Intelligence (BI)

Harrison Holgate
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst Senior Consultant, Assistant Manager, Manager - Belfast

RQ1688775 - Data Quality and Systems Manager

Manager Quantitative Analysis - Centre for UK Growth

Manager Quantitative Analysis - Centre for UK Growth

Manager Quantitative Analysis - Centre for UK Growth

Manager Quantitative Analysis - Centre for UK Growth

Senior Business Development Manager - Business Intelligence (BI)

London

Reference: HH/RF-13612

Position: Senior BDM - Business Intelligence (BI)

Salary: Up to £80,000 + Car Allowance + Commission

Location: City of London

I am supporting a leading international insurance organisation as they expand their commercial presence through BI sales, seeking an ambitious Business Development Manager to drive new business growth across mid-corporate clients (€50m–€500m turnover).

You will be responsible for generating and converting new business opportunities, developing your own pipeline through proactive prospecting, and building strong relationships with senior financial decision-makers and key introducers.

Key responsibilities include:

  • Winning new logos and achieving individual revenue targets.
  • Prospecting through networking, outreach and marketing-generated leads.
  • Building awareness of the organisation’s Business Information and credit-related solutions
  • Developing partnerships with brokers, introducers and strategic contacts.
  • Managing RFPs, negotiating terms and closing deals.
  • Producing accurate contract documentation and completing KYC/UBO checks.
  • Collaborating with commercial, marketing and support teams to ensure seamless client experience.
  • Providing regular activity reporting and market insights.

About You:

  • Strong experience selling Business Information, financial data or risk solutions.
  • Proven success selling into mid–large corporates, hitting targets.
  • Confident self-starter with experience generating your own leads.
  • Excellent relationship-builder, communicator and negotiator.
  • Strong commercial judgement with understanding of contract structures and financial analysis.

For more information please apply:

-

-

As true market specialists we work in partnership with our candidates and clients, delivering unrivalled market knowledge and insight. Driven by our passion to become the partner of choice we offer tailored advice and guidance...


#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.

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.

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.

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.