Senior Product Manager, Ranking Team

Griffin Fire
London
2 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Manager

Machine Learning Engineering Manager

Senior Data Developer

Senior Data Engineering Manager

Data Science and Analytics Senior Business Analyst

Senior Product Manager - AI, ML & Data Science

Constructor is the only search and product discovery platform tailor-made for enterprise ecommerce where conversions matter. Constructor's AI-first solutions make it easier for shoppers to discover products they want to buy and for ecommerce teams to deliver highly personalized experiences that drive impressive results. Optimizing specifically for ecommerce metrics like revenue, conversion rate and profit, Constructor generates consistent $10M+ lifts for some of the biggest brands in ecommerce, such as Sephora, Petco, home24, Maxeda Brands, Birkenstock and The Very Group. Constructor is a U.S. based company that was founded in 2015 by Eli Finkelshteyn and Dan McCormick. For more, visit: constructor.io.

Below, you will find a complete breakdown of everything required of potential candidates, as well as how to apply Good luck.We are seeking an exceptional Product Manager who can dive deep into engineering to understand technical challenges and constraints; work with sales to understand prospective customer’s pain points; and coordinate ideal messaging with marketing -- all while maintaining focus on our customers.This person will be as talented at communication as they are at analysis and user discovery. Recognizing that a product manager is more effective at leading through persuasion than decree, this individual is an expert in artful communication across functional roles, teams, and personalities to influence company trajectory. Furthermore, the ideal candidate should be just as comfortable discussing searches internally as they are with external partners and current or prospective customers.Day-to-day you will:Create and socialize a compelling roadmap that translates into an iterative and value-driven backlog.Orchestrate go-to-market activities with sales and marketing.Conduct customer and user interviews to better understand pain points and product opportunities.Drive cross-team coordination and collaboration with your fellow Product Managers to maximize delivered customer value.Work to support major new customer onboarding where necessary.Perform competitive research and analysis, and regularly report it back to the team.Research market trends, and make sure we're planning for where the market will be in a few years, not just today.Drive product definition, strategy, long long-term vision and you have the autonomy to go after the largest opportunities, regardless of where they fall within the user journey.You would be a good fit if:You have 2 years of experience leading the definition and delivery of products/features/projects that have a high degree of cross-functional complexity and integration.You have worked directly with Machine Learning teams for more than 2 years.You seek an entrepreneurial environment and have a track record of delivering results in a high-growth environment.You have excellent analytical abilities and can effectively use data to drive decisions.You are motivated to deliver value in production and aren't satisfied with works-in-theory solutions.You have experience running products in a B2B SaaS context or think you can learn the ropes quickly enough.You are collaborative, value learning, and are driven to accomplish great things.You are excited to bring learnings from your experience to augment our product culture.You have demonstrated success working with teams including a significant number of remote and distributed members, particularly in engineering roles.Familiarity working in an agile software development environment with empowered teams.At Constructor we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group.Benefits include:Unlimited vacation time - we strongly encourage all of our employees to take at least 3 weeks per year.A competitive compensation package including stock options.Fully remote team - choose where you live.Work from home stipend! We want you to have the resources you need to set up your home office.Apple laptops provided for new employees.Training and development budget for every employee, refreshed each year.Parental leave for qualified employees.Work with smart people who will help you grow and make a meaningful impact.Diversity, Equity, and Inclusion at ConstructorAt Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications.

#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.