Operations Strategy Specialist

Snap Finance UK
Milton Keynes
2 months ago
Create job alert

JOIN A DYNAMIC TEAM THAT’S DRIVEN TO CREATE THE IMPOSSIBLE AND GET STUFF DONE!


Do you thrive on solving complex problems, optimising processes, and making things run smoother and faster? Want to be part of a high-energy team that’s revolutionising the Retail Point-of-Sale Finance industry?


We’re looking for an Operations Strategy Specialist who can take our operational processes to the next level while keeping customer outcomes front and centre. This role is all about strategy, efficiency, and impact—you’ll develop and implement smart, scalable solutions to improve contact management, automation, system administration, and data visibility.


Who are we and what do we do?

Snap Finance UK is a rapidly growing FinTech company focused on digital disruption and inclusivity in the financial services industry. Snap’s proprietary technology platform and decisioning algorithms are changing the face and pace of consumer retail finance. Our use of technology has been recognised and Snap has recently been awarded the UK's Best Use of Technology in consumer lending at the Credit Awards 2024. Snap has a strong, supportive culture and is dedicated to its customers, retail partners, and its people who are at the heart of our business. Snap Finance UK was established in 2017 and is based in Milton Keynes, with the backing of its parent company, founded in the United States in 2012.


Reporting to:Operations Improvement Manager

Location:Crownhill, Milton Keynes / Hybrid Working (at least 2-3 days in the office per week)


What you’ll be doing:


Data Visibility & Reporting

  • Drive data visibility strategies and develop dashboards to track key operational metrics.
  • Create detailed, data-driven reports to inform decision-making and performance improvements.
  • Ensure actionable insights are communicated effectively across the business.
  • Collaborate with teams across analytics, finance, commercial, and technology to align operational strategies with business goals.
  • Validation of data integrity (Call classification and outcome monitoring)
  • Use data visualisation tools to clearly communicate insights to stakeholders.
  • Leverage data insights to forecast capacity needs, identify bottlenecks and propose potential solutions. (e.g., automation)



Contact Strategy Development

  • Develop and optimise multi-channel customer contact strategies (phone, email, SMS, chat)
  • Use data insights to drive engagement and improve response times.
  • Work with customer service and collections teams to enhance communication effectiveness.
  • Conduct capacity planning and productivity analysis across teams.
  • Monitor and optimise automation performance in real-time.


Process Optimisation

  • Evaluate operational systems to identify efficiency gains and improvement opportunities.
  • Work cross-functionally to integrate process improvements aligned with business objectives.
  • Design scalable operational processes to support business growth.
  • Work with tech teams to ensure full system integration and continuous improvement of automation tools.


System Administration

  • Manage internal business systems to ensure seamless integration and accurate, timely data.
  • Provide system support and troubleshoot to ensure operational teams have full data visibility.
  • Maintain system compliance and performance monitoring.
  • Managing workflows and campaigns across operations


Daily and Ad-hoc Duties

  • Manage daily campaigns
  • Provide accurate and informative insights whilst challenging the data and making recommendations for improvement
  • Analyse day to day stats in real time
  • Resource & planning for the operations teams
  • Support the integration of new systems
  • Manage the administration of key systems used within the department
  • Work to continuously improve our contact strategy maximising all touch points of the customer journey
  • Liase with the analytics team to ensure data integrity


To succeed in this role, you should bring:


  • Proven experience in operations strategy, process optimisation, or business operations within a similar industry (e.g., POS Finance, FinTech, or financial services).
  • Strong numeracy and analytical skills, with the ability to interpret large volumes of data, develop insights, and make data-driven decisions.
  • Experience with data visualisation tools (e.g., Tableau, Power BI) to track and report on operational performance and KPIs.
  • Expertise in contact strategies and customer engagement in a multi-channel environment, using data to measure success and inform strategy.
  • Experience with system administration and managing internal operational software tools (CRM, ERP, etc.).
  • Working knowledge of automation tools and technologies (e.g., Robotic Process Automation, AI-powered systems, workflow automation).
  • Ability to manage complex projects, with a focus on execution, timelines, and data-driven results.
  • Strong communication and stakeholder management skills, with the ability to present data and insights to leadership in an actionable manner.
  • Strong analytical and problem-solving skills with a focus on data-driven decision making.
  • Comfortable working in a fast-paced, data-driven environment, adapting to changing priorities based on insights and business needs.



What’s in it for you?


Joining Snap Finance means becoming part of a forward-thinking, ambitious, and supportive team. We offer:

  • Competitive salary and opportunities for professional growth
  • Flexible hybrid working arrangements to balance your work and personal life
  • Access to our comprehensive benefits package, including private healthcare, discounted gym memberships, and more
  • A collaborative and innovative work environment where your ideas and contributions make a real difference


If you’re excited about this opportunity and think you’re the perfect fit, hit ‘APPLY’ and upload your CV and cover letter today. Please note that all successful applicants will be subject to a basic criminal record and credit check.

Related Jobs

View all jobs

Head of Sports & Trading

Health data specialist

Senior Director, Data Governance Operations | England - London

CRM and Data Manager (Italian-speaking)

IT Service Management Lead

Data Governance Lead

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.

Data Science Jobs for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.

Data Science vs. Data Mining vs. Business Intelligence Jobs: Which Path Should You Choose?

Data Science has evolved into one of the most popular and transformative professions of the 21st century. Yet as the demand for data-related roles expands, other fields—such as Data Mining and Business Intelligence (BI)—are also thriving. With so many data-centric career options available, it can be challenging to determine where your skills and interests best align. If you’re browsing Data Science jobs on www.datascience-jobs.co.uk, you’ve no doubt seen numerous listings that mention machine learning, analytics, or business intelligence. But how does Data Science really differ from Data Mining or Business Intelligence? And which path should you follow? This article demystifies these three interrelated yet distinct fields. We’ll define the core aims of Data Science, Data Mining, and Business Intelligence, highlight where their responsibilities overlap, explore salary ranges, and provide real-world examples of each role in action. By the end, you’ll have a clearer sense of which profession could be your ideal fit—and how to position yourself for success in this ever-evolving data landscape.