Senior Product Manager - Retention

Jobleads
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Product Manager - AI, ML & Data Science

Senior Machine Learning Product Manager (Deploy)

Product Manager

Senior Machine Learning Engineer

Senior Data Scientist

Machine Learning Manager

We are looking for a Senior Product Manager to help drive M-KOPA’s mission of building transformative lifetime financial partnerships with our customers.

This role offers the opportunity to drive significant customer and business impact through the implementation and iteration of critical engineering systems, internal tooling, and business processes. You'll work with talented cross-functional teams including engineers, data scientists, analysts, designers, and commercial stakeholders across multiple countries.

About Us

We foster a low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact. Our team values psychological safety and takes a discovery-first approach to problem solving. You'll be empowered to make data-driven decisions and clear cases for prioritization of solutions in a domain that you have a high degree of ownership over.

We are looking for a technical and/or analytical PM for this role — if you have a fondness for engineering and/or you love digging into data, you might be a good fit!

In this role, you would be responsible for:

  • Owning the strategic direction and evolution of critical engineering systems and business processes
  • Working with engineers to drive continuous improvement in our systems’ capabilities
  • Partnering with data scientists and analysts to understand user needs and implement novel methodologies
  • Getting feedback from customers and customer care teams to understand customer pain points
  • Analyzing data to understand the largest areas of opportunity for further improvements

This is afully remote roleand will include travel across our different markets and working within theUTC -1throughUTC+3 time zones.

Your application should demonstrate:

  • 5+ years of product management experience
  • Strong technical and/or analytical skills, including the ability to conduct your own complex data analysis
  • Proven ability in solving technical and/or analytical problems
  • Ability to work with diverse, distributed teams across multiple countries
  • Strong interpersonal, communication, and collaboration skills
  • Experience in data-driven decision making and strategy development
  • Experience with agile methodologies and cross-functional team leadership
  • Nice to have: Experience with data science models

If the above is of interest to you, please apply.

Why M-KOPA?

At M-KOPA, we empower our people to own their careers through diverse development programs, coaching partnerships, and on-the-job training. We support individual journeys with family-friendly policies, prioritize well-being, and embrace flexibility.

Join us in shaping the future of M-KOPA as we grow together. Explore more atm-kopa.com.

#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.