Data & Analytics Lead Analyst

LAGOFIRE SRL
Bristol
2 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Data Analyst/ Consultant (SuccessFactors, MS Excel, Mapping)

Business Intelligence and Reporting Analyst

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

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.