Head of Data Analytics

JLA Group
Ripponden
1 week ago
Create job alert

JLA has been providing critical assets and services to a range of businesses and sectors including Care Homes, Hospitals, Schools, and Hotels for over 50 years. These assets and services are crucial in supporting customers with their Laundry, Catering, Heating, Fire Safety, Infection Control, and Air Conditioning.

The company offers a unique, all-inclusive package called Total Care, this rental model allows customers to make a single monthly payment, to receive brand new equipment, and have maintenance costs taken care of.

Role overview

As Head of Data Analytics, you will lead our data strategy and analytics capability, enabling smarter, faster decision-making across the organisation.

You will oversee data governance, advanced analytics, and insight delivery – transforming how the business uses data to understand customers, markets, and performance.

You will lead a team of analysts to (a) gather and interpret data to inform strategic and operational decision making, and (b) segment data and present data so that it can be used for outbound marketing campaigns activated via telemarketing and email channels.

Role cohort:

  • Campaign Effectiveness Manager
  • Campaign Analyst
  • Data Analyst
  • Supply Chain Analyst
Key tasks
  • Develop the marketing intelligence and insight strategy. Define the marketing intelligence roadmap ensuring that data underpins marketing and commercial decision making.
  • Design segmentation. Develop customer segmentation and value-based marketing models, defining priority audiences by needs, behaviour, and commercial potential.
  • Enhance data. Lead data enrichment, acquisition, and insight programmes to continuously improve the quality and reach of our customer database.
  • Deliver customer insights. Analyse customer behaviour, feedback, and churn dynamics to inform decisions on retention, acquisition, and optimising the customer lifecycle.
  • Create and manage data-led campaigns. Developing high quality, compliant data lists for use by telemarketing and sales teams to drive lead generation and conversion activity.
  • Generate reporting that drives ROI. Build and maintain marketing dashboards and reporting frameworks that provide visibility of campaign, segment, and market performance.
  • Lead a team. Lead and develop a team of analysts and insight specialists to deliver actionable intelligence at speed and scale.
  • Work across the business. Partner with marketing, sales, operations, customer, and technology teams to translate insight into actionable strategies.
  • Champion data. Drive adoption of BI tools, data literacy, and self-service analytics across the business, championing data literacy and curiosity across the marketing team, embedding a culture of informed, evidence-based decision making.
Knowledge and Skills
  • Proven leadership experience in marketing and data analytics, business intelligence, customer insight and marketing operations.
  • Proven ability to design and deliver data-led marketing campaigns that feed into telemarketing or inside sales teams.
  • Strong understanding of segmentation, campaign targeting, and CRM data management
  • Experienced in using BI tools (Power BI, Google Data Studio) and CRM / marketing automation platforms (Salesforce, Dynamics, HubSpot etc.)
  • Proficient in SQL.
  • Strong commercial mindset with the ability to link data insight to business outcomes
  • Deep technical expertise in analytics platforms, data visualisation tools, and statistical modelling.
  • Experience in service-orientated and commercial B2B sectors is an advantage.
Experience
  • 10 years’ experience in data and analytics.
  • 5 years’ experience in lead generation.
  • Experiencing of leading a team.
  • Excellent stakeholder management and communication skills.
Benefits

When you join the JLA family, you'll also gain access to an extensive benefits package.

We care about our people and take your well-being seriously, which is why we offer a range of supportive tools for health and wellbeing, financial guidance, and legal advice. Our Employee Assistance Programme, 24/7 Wellness and Lifestyle App plus a dedicated team of Mental Health First Aiders are there to support you through life's challenges. We also offer up to 8 counseling sessions, which can be in-person or remote, providing you with the support and flexibility to suit your own personal needs. You can reach any fitness goals with our free onsite gym at head office along with a range of other gym membership discounts available.

To offer financial support, we not only provide life assurance coverage, company sick pay, and a company pension scheme, we offer a range of added benefits such as free office parking, eye care vouchers, a cycle-to-work scheme, and exclusive discounts through our staff benefits hub.

We really pride ourselves in offering a healthy work-life balance and believe it is important to have time away to recharge which is why we provide 25 days of annual leave plus bank holidays, flexible working options, and enhanced family leave policies.

We are a company that appreciates you and invests in your success and even have a Colleague Recognition Scheme to celebrate your achievements. We're dedicated to your growth, offering support in career development and training. We value your referrals, and through our Refer a Friend scheme, you can earn up to £1,000 in bonus rewards!


#J-18808-Ljbffr

Related Jobs

View all jobs

Head of Data Analytics

Head of Data Analytics and Insights

Head of Data Analytics & Marketing Insights

Head of Data Analytics

Head of Data Analytics and Transformation IH

Head of Data Analytics and Transformation IH

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.