Data & Analytics Lead Analyst

LAGOFIRE SRL
Bristol
10 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Analyst

Lead Data Analyst

Analytics Specialist with Data Science

Data Scientist

Senior Data Analyst

Lead Data Engineer

Description

We use innovation to shape data so it works for everyone and we're planning to re-platform and improve the existing (commercial, operational and customer) data assets and develop new ones, as well as transform how we work with the business to use our data better.

In this role you will combine hands-on development in cloud-based technologies, alongside direct management of a team of multi-skilled data analysts and data scientists delivering key data solutions. Your creative approach to problem solving using data and technology will delight your customers and encourage them to share their curiosity and motivation for data-driven solutions.

We're looking for a data enthusiast, able to turn data into insights so they flow consistently across MO and shape our thinking to drive a culture of customer-focused, evidence-based decision making. You have the important task to support adoption and use of Data and Analytics (D&A) services and products across MO. You will help raise the level of data literacy to support employees to become more data-driven and discover the value of D&A.

A natural storyteller, you will work across MO forging strong connections with stakeholders, proactively driving awareness and helping them to use data and insight to improve their ways of working within their roles. You have experience in a data-related role, possessing a proven foundation in programming (Python and SQL) and a passion for redefining data into actionable insights.

Qualifications

About you

This is a great opportunity for an experienced data leader to join a well-established and successful team to contribute to and enhance their internal data capabilities. It is an ideal role for someone who has, or is able to;

  1. Held a lead role where you have successfully delivered data-focused solutions using ETL and BI tools in part of an Agile development team.
  2. Been in a team management/leader or mentoring position responsible for the development of team members through holding regular review meetings, setting personal objectives, and career development plans.
  3. The ability to inspire and motivate to bring the best out of individuals and as a team through coaching and sharing technical knowledge.
  4. Excellent skills in data visualization and the ability to communicate complex analytical findings to both technical and non-technical stakeholders.
  5. Demonstrated experience in turning analytical insights into actionable recommendations for business support and leadership.
  6. Ability to work closely with the data engineering team and collaborate with various partners to provide actionable insights and analyses.
  7. Experience in data transformation and designing data products.
  8. Ability to support product owners and work in a cross-functional data & analytics team.
  9. Comfortable organizing data and transforming it into meaningful insights and recommendations.


Minimum Criteria

You'll need all of these.

  1. Proven experience in business intelligence, data analytics, data science, or a related field.
  2. Experience/familiarity with Oracle, Snowflake, or similar.
  3. Strong knowledge of data management principles, database systems, and data warehousing concepts.
  4. Strong command of SQL, for querying and managing relational databases.
  5. Proficiency in business intelligence tools and technologies (e.g., OAS, PowerBI).
  6. Understanding of machine learning or data science.
  7. Excellent communication and interpersonal skills, with the ability to effectively collaborate with stakeholders in multiple offices.
  8. An innovator who constantly helps MO improve efficiency and growth through data insights, has an analytical mindset, and has problem-solving abilities, focusing on delivering actionable insights.


Plus points if you have experience working across multiple data sources. You have successfully created data products within Agile development teams and possess a good understanding of data science principles and practices.

Benefits

Motability Operations is a unique organisation, virtually one of a kind. We combine a strong sense of purpose with a real commercial edge to ensure we provide the best possible worry-free mobility solutions to over 815,000 customers and their families across the UK. Customers exchange their higher rate mobility allowance to lease a range of affordable vehicles (cars, wheelchair accessible vehicles, scooters, and powered wheelchairs) with insurance, maintenance, and breakdown assistance included. We are the largest car fleet operator in the UK (purchasing around 10% of all the new cars sold in the UK) and work with a network of around 5,000 car dealers and all the major manufacturers. We pride ourselves on delivering outstanding customer service, achieving an independently verified customer satisfaction rating of 9.8 out of 10.

Our values are at the heart of everything we do. They represent ambition, and we look for our people to live and breathe them every day:

  1. We find solutions.
  2. We drive change.
  3. We care.


We operate hybrid working across the organisation where we split our time between working on-site at our offices and at home, remotely within the UK. We believe hybrid working achieves a good work/life balance for our colleagues, allowing us to connect with each other, collaborate on important work, and perform together to deliver for our customers. It allows us to have the flexibility to work remotely up to 2-days per week whilst also using the great office spaces we have available.

As a Motability Operations team member, the benefits you can expect are:

  1. Competitive reward package including an annual discretionary bonus.
  2. 15% non-contributory pension (9% non-contributory pension during probation period).
  3. 28 days annual leave with option to purchase and sell days.
  4. Free fresh fruit and snacks in the office.
  5. 1 day for volunteering.
  6. Funded Private Medical Insurance cover.
  7. Electric/Hybrid Car Salary Sacrifice Scheme and Cycle to Work Scheme.
  8. Life assurance at 4 times your basic salary to give you peace of mind that your loved ones will receive some financial help.
  9. Funded health screening for over 50s.
  10. Voluntary benefits: charitable giving, critical illness insurance, dental insurance, health and cancer screenings for you and your partner, discounted gym memberships, and season ticket loans.
  11. Employee Discount Scheme with an app to save on the go.
  12. Free access to healthcare apps such as Peppy, Unmind, Aviva Digital GP and volunteering app on Hand for all employees.
  13. Generous family leave policies.


At Motability Operations, we believe in building a diverse workforce, where our people are empowered to attend work as their true selves, and we encourage people from all backgrounds to apply. We want to sustain a culture that nurtures, where employees are free to flourish and where they're rewarded equally, regardless of race, nationality or ethnic origin, sexual orientation, age, disability, or gender.

We pride ourselves on being an inclusive employer and as such, all our offices provide first-rate disability access. With our hybrid working environment, we do our best to accommodate part-time and flexible working requests where possible, building on our culture of trust, empowerment, and flexibility.#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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.