Data Analytics Manager

Hemel Hempstead
11 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst in Luton)

Research Manager (Analytics/Data Science)

Research Manager (Analytics/Data Science)

Data Analyst

Data Engineer Manager

Data Engineering Manager

Data Analytics Manager

We have a fantastic new opportunity for a Data Analytics Manager to join our Business Support Team at Hightown Housing Association!

The Data Analytics Manager will be responsible for developing and delivering the Associations Data & Information Management Strategy, supporting effective data governance, management, efficiency and enhanced reporting. You will lead a team of data analysts that provide high quality insights and provide users with information to guide both operational performance and strategic direction.

As well as technical skills, the post requires strong project management skills and requires the ability to problem-solve, prioritise, and communicate.

The successful candidate will have:

3 to 4 years' experience using data visualisation tools e.g. Tableau, Power BI
Knowledge and experience in relational database concepts, design, constraints, stored procedures, functions and optimization
The ability to collate, produce and submit various KPI reports to both internal and external stakeholders, supported by agreed definitions and data sources
The ability to lead the team in performing regular audits and quality assessments of data to identify areas for improvement, working with data owners to improve the source information
The knowledge to collate technical specifications that translate business needs into technological solutions that maximise data and information from a variety of sourcesIt’s essential that you hold a Full UK Driving License and have access to a car for work purposes.

About Us

Hightown is a charitable housing association operating principally in Hertfordshire, Bedfordshire, Buckinghamshire and Berkshire. We believe everyone should have a home and the support they need, so our aim is to build new homes and to provide excellent housing and support.

We currently manage over 9,000 homes and employ over 1100 Permanent and Bank staff in our Care and Supported Housing Schemes and from our head office in Hemel Hempstead. We have an annual turnover of £121 million and a development programme that will deliver over 350 new affordable homes each year.

Benefits

We offer a range of benefits which include:
• Generous annual leave allowance of 33 days per year, including statutory bank holidays, rising to 35 days with service
• £65,000 pa for a 35 hour a week contract
• • Annual bonus based on satisfactory performance (Dependant on start date and contract length)
• Monthly attendance bonus on top of your basic salary
• Commitment to health and wellbeing with the Five Ways to Wellbeing
• Ongoing professional development and support to deliver outstanding support
• Workplace pension scheme and life assurance of three times your annual salary
• Refer-a-friend scheme: Earn a £130 bonus for each friend you refer to work for us
• Employee assistance helpline
• Mileage paid for car usage
• Free well-equipped onsite gym

Closing date: Sunday 9th March 2025

Please note that we will be shortlisting and interviewing candidates on an ongoing basis and therefore we may close the vacancy early. Interested applicants are therefore encouraged to apply as soon as possible to ensure they are considered.

We are an Equal Opportunities & Disability Confident Employer.

To stay safe in your job search we recommend that you visit SAFERjobs, a non-profit, joint industry and law enforcement organisation working to combat job scams

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.