Senior Product Marketing Manager

James Adams
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Director, Data Science and Analytics

Senior Data Analyst

Senior Data Engineer

Associate Product Data Analyst

Data Science Manager (Metaheuristics)

Data Science Manager (Metaheuristics)

Role: B2C Product Marketing Manager - FTC 12 Month Maternity Cover


Remote:

  • Based anywhere in the UK or Europe
  • Monthly commute to Paris (all travel expensed)


Location: Office HQ in Paris


Salary:£85,000-£95,000based on experience + £1000 monthly learning budget + many other perks!


James Adams is recruiting for 12 Month FTCSenior Product Marketing Managerto join one of our clients for a 12 month FTC. They are a fast-growth startup and launched a leading mobile app, which has over 8million monthly users across 180 countries.


They utilise cutting-edge technology that empowers entrepreneurs, small businesses, and merchants to easily create images that sell without any training, using deep learning to translate pixels into objects, simplifying tasks such as removing backgrounds from images or removing objects. They're looking for aProduct Marketing Managerto join them on a 12 month FTC, helping our client building thego-to-market strategiesandeducating the teamson improvements they should make to the product that will reachmillions of users across the globe!


Our clientoffers remote workingwith a once-a-month or more (fully reimbursed) trip to their office in Paris!


As Product Marketing Manager you will:

  • Communicating product to users
  • Championing customers and understanding audiences
  • Converting co-workers (across the development, marketing and product teams) into product advocates
  • Assisting with product growth
  • Ensuring the product is tied closely to brand identity-You will be working with the Head of Brand to ensure the product resonates with the prosumer audience!
  • Creating and building the Go-To-Market plan-You are adaptable and will be constantly iterating improvements to the product based on user research and competitor analysis, by educating the teams on key findings you uncover when working closely with a researcher
  • You will be creating video content for user interviews and product content!


What you will bring to this role as Product Marketing Manager:

  • Strong video content creation skills for user interviews and product content
  • Strong background in B2C Product Marketing with a strong focus on aprosumer audience, freemium models and or mobile apps!
  • E-commercebackground.
  • Impeccable communication and solid collaborative skills.
  • You have experience conductinguser and competitorresearch
  • You have an independent work style and strong product opinions!
  • You have proven experiences working across a business and deliveringinternal product education to teams.


Our client is flexible offering remote work from anywhere in Europe but is ideally looking for English speakers as the whole team speak English as the main language. They work on a fully remote basis but do monthly/quarterly meet-ups in Paris, all travel expenses will be paid for, for these meetings.


The founder team come from businesses likeApple, Algolia, Google, or Bumbleand if you want to work with theGrowth and Marketing teamfor the one of the biggest B2C mobile app, apply now!

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.