Process Mining Lead - Senior Manager

KPMG
Newcastle upon Tyne
1 month ago
Applications closed

Related Jobs

View all jobs

Lead, Data Scientist (Deep Learning), Peacock Video Streaming Service

Kuiper Consumer Senior Data Scientist, Project Kuiper

Principal Data Scientist

Data Scientist

Data Science Placement Programme

Data Science Placement Programme

Job description

Process Mining Lead - Senior Manager

 

KPMG Overview

KPMG in the UK is part of a global network of firms that offers Audit, Legal, Tax and Advisory services. Through the talent of over 16,000 colleagues we bring our creativity, insight and experience to solve our clients’ and communities’ biggest problems. We’ve been doing this for more than 150 years. We aim to be universally recognised as a place for great people to do their best work. A firm known for our collaborative and inclusive culture, using technology to empower and equip our people to deliver outstanding work with real flexibility – through inspiring workspaces, innovative ways to collaborate and hybrid ways of working. With offices across the UK, we work with everyone from small start-ups and individuals to major multinationals, in virtually every industry imaginable. Our work is often complex, yet our mission is simple: To support the UK in a connected world. It guides everything we do, underpinned by our values: Courage, Integrity, Excellence, Together and For Better.
 

Role Overview

As a Process Mining Lead - Senior Manager, you will be responsible for designing solutions, to address business demand and have a strong focus on developing pipeline, pre-sales, sales and contract creation. In your roles as Senior Manager, you’ll work with Project Managers and Development teams to guide the design through to delivery, ensuring that KPMG quality and risk frameworks are adhered to. You will work in a rapidly developing team, with ambitious growth intentions, to help establish a world leading capability. You will be challenged to maintain your knowledge around the market segment, whilst developing technical breadth and depth of knowledge across numerous other interface layers

 

Responsabilities: 

Deliver solutions which meet KPMG’s quality framework, whilst leveraging Appian best practises Identify, develop and land sales and project opportunities with clients, both new and existing, to deliver our propositions Be responsible for developing our Architecture patterns and Best Practices Have responsibility for maintaining our platforms and their integrations with other services / platforms Ensure our platforms remain compliant with required standards of Information and Data Security Proposing technical and creative business solutions Working in a DevOps model to support in flight solutions, whilst innovating on new opportunities Help identify new go to market opportunities for the Process & Automation Team Deliver showcases to clients and internal stakeholders, to help establish wider awareness of Process & Automation capabilities Designing and delivering high quality technical Proof of Concepts for prospective customers To have an up to date view of the roadmap of features for the technologies we use, and be able to articulate them
 

Leadership & Management:
As a Senior Manager you will be responsible for driving the training and certification of the team forward and managing junior architects. Establishing KPMG as a trusted partner for Technoloogy solutions.


Stakeholder Interaction & challenges:
Joining KPMG means joining a talented team of exceptional colleagues who bring innovative thoughts and a natural curiosity to the work they do each day. No one type of person succeeds at KPMG; a diverse business requires diverse personalities, characters and perspectives. There really is a place for you here. 


Impact, Risk, Accountability & Governance:
Will be expected to support existing solutions that Process & Automation already has out in the market.

Technical skills 

Minimum of 5 years experience in designing Solutions, UX/UI, Process Model design Minimum 5-10 years experience as a Solutions Architect In depth experience/knowledge of architecture best practises In depth experience and knowledge with Cloud based architectures (AWS, Azure, Google, Private Cloud) Experience working with Virtualisation technologies (e.g. Docker, Kubernetes) Experience working micro-service, analytics and messaging architectures (e.g. Quantexa, Kafka, NodeJS/Python microservices) Experience working in CI/CD and DevOps environments Experience with relational and non-relational databases Recent experience programming in one or more of the following: Java (J2EE, JNDI, JDBC, JMS, Web Services), HTML, XML, XSL, JavaScript, SQL. Ability to identity the benefits between different hosting platforms, from on premise server installs through Hybrid, to Cloud hosted agnostic Experience in production environments (application servers, web servers, databases)

 

Non-technical skills

Extensive experience of a variety of development methodologies (e.g. Scrum (and other Agile methodologies), Kanban, ScaledAgile, XP, Waterfall etc) Extensive experience of the Software Development Lifecycle (SDLC) Experience in/Exposure to Defect Management, Change Management, Release Management, Information Security Experience in Pre-Sales, Sales, pipeline management, contract creation and engagement management Already have, or be eligible for, SC Clearance Desire to strive for continuous improvement Ability to translate business requirements into user stories Experience in a delivery role, working to timeline and budget requirements Able to thrive in a unique culture where thinking outside of the box is required daily and creative input is necessary to solve business problems Technical depth to understand the landscape of the complete solution Proven success conveying customer requirements to Product Management teams Familiarity with Business Process Management Languages and Platforms/Frameworks: Appian, PegaSystems, Outsystems, Mendix, etc Familiarity with Process Mining technologies such as Celonis, Aris, Signavio, etc Familiarity with RPA tools such as BluePrism, UIPath, Automation Anywhere etc. Strong verbal and written communication skills, customer interaction, requirements analysis, presentations, and system design

 

Nice to have experience
Technical skills 

Experience with cognitive services integrations (Azure, Google, IBM) Data Visualisation – Qlik, Dataiku, Tableau, PowerBI OCR (Kofax, Kodak, Xerox, Computer Vision, Microsoft Cognitive Services etc.)

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.