Marketing Data Analyst

Landbeach
9 months ago
Applications closed

Related Jobs

View all jobs

Marketing Data Analyst

Marketing Data Analyst

Commercial Data Analyst

Senior Data Analyst

Data Analyst Marketing

Lead Data Analyst

Marketing Data Analyst

Location: Cambridge or London

Salary: £25,000 - £40,000

Permanent, full time (optional 9 day fortnight working pattern available)

Closing Date: 13th June 2025

We are looking for a Marketing Data Analyst join us!

Further Key Responsibilities:



*

Data Management: Collect, organize, and analyze contact and opportunity data to identify trends, patterns, and insights that can drive business decisions.

*

Business development reporting (opportunity tracking)

*

Reporting and Analysis: Develop reports and dashboards to support ongoing marketing performance and adoption within the business. Also to monitor the effectiveness and make recommendations for improvements.

*

Customer Segmentation: Utilize data to segment customers based on demographics, behaviors, and preferences, enabling targeted marketing campaigns.

*

Collaboration: Work closely with marketing, finance and BD team to ensure that CRM data is effectively leveraged across the organization.

*

System Management: Assist in the maintenance and optimization of CRM software systems, ensuring data accuracy and consistency.

*

Compliance: Ensure that CRM practices adhere to data protection regulations and company policies.

Essential skills and experience

*

Bachelor’s degree or significant relevant experience in Business, Marketing, Data Science, or a related field.

*

Experience using CRM systems (preferably Hubspot), data management, or a related field.

*

Familiarity with industry standards and best practices in contact-data management.

*

Experience in managing CRM projects and initiatives.

*

·Strong analytical skills with the ability to interpret complex data sets and provide actionable insights.

*

Experience and proficiency in CRM software and data analysis tools (direct experience in Hubspot is ideal, Microsoft Dynamics).

*

Strong MS Excel capability is also essential. Experience of coding desirable.

*

·Excellent written and verbal communication skills to convey data-driven insights to stakeholders.

Firm culture is important at Stobbs - friendly, social, approachable and where we look after each other. We regularly provide our own social and professional events. We manage the rights of some fantastic clients - obviously that means our advice has to be legally sound, but it's also about it being business savvy. We have high standards but learn from our mistakes. We’re not internally competitive (well, except when it comes to sports and quizzes!). We're certainly not run with an iron fist; we want our people to bring their whole selves to work, wanting to perform well, learn from mistakes and to feel comfortable asking questions and learning, and helping us continue to improve and be the best we can be.

Our head office is north of Cambridge, with an office in central London. We are trying to strike a good balance of supporting people to work flexibly while delivering for our clients and making Stobbs an attractive place to work. Our current hybrid working policy is a minimum requirement of two days in the office, encouraging people in more if possible. We may expect you to be based in the office full-time during the first six-months. Those seeking a part-time role may also be considered.

The company

Stobbs is a niche intellectual property practice that recognises that to give the best advice on brands, you need to take a more strategic and holistic approach than pure trade mark expertise. To that end, we launched the concept of Intangible Asset Management.

We have a breadth of capability that goes far beyond the scope of any other IP firm and encompasses trade marks, designs and copyright, litigation, disputes, commercial contracts, brand intelligence, brand extension (licensing), systems, online brand enforcement, anti-counterfeiting and brand restructuring.

Formed in 2013 with 18 people, today we have over 200 professionals based in Cambridge, London, Dublin, Eindhoven and Munich

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.