Product Manager, EHS&S

Sphera
remote, great britain
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Scientist

Data Scientist

Settlements Data Analyst

Senior Data Scientist

Data Engineer

The Opportunity
We are looking for a Product Manager to join the Sphera team to act as the empowered central point of product leadership. They will act as the messenger of the market and the voice of the customer for the organization. They are responsible for the continuous delivery of value to the market, customers, and users. They engage their stakeholders in making data-driven decisions regarding which new products, features, and functionality to build and the order in which to build them. The product manager is responsible for the entire product lifecycle and the overall success of their products in the market. They are responsible for collaborating with their teams to rapidly build the solutions our customers and the market need.

How you’ll spend your day:

Gather market intelligence; serve as the messenger of the market and voice of the user for the rest of the organization. Lead data-driven decisions regarding product development priorities with consideration for customer value and feasibility. Build, maintain, and communicate a product roadmap with internal and external stakeholders. In collaboration with your cross-functional product team, continuously deliver innovation that will delight users and grow our business. Understand and support your sales and customer success teams; enable sellers and account managers to understand the problems you solve for your buyers and users; partner with the sales training team to develop internal tools and with marketing communications to develop external collateral. Help your customers achieve their environmental, health, safety, and sustainability goals through innovation.

What makes you a great fit:

A strong communicator, excellent writer, and enthusiastic presenter Strong leadership skills and a bias toward action Empathy, humility, curiosity, and business acumen 3+ years of product management or similar experience including all aspects of managing the product lifecycle and an agile SDLC Bachelor’s degree in business, marketing, computer science, or a related field is preferred Pragmatic Institute Certificate (PMC) II or higher is a bonus Experience in Environment, Health, Safety, and Sustainability (EHS&S) is preferred Experience in data science, machine learning, or generative AI is preferred Experience working with remote colleagues using conferencing tools Travel up to 10% of the time to meet clients and your teammates

#LI-CS1

Pay:

$112,000.00 - $168,000.00 + Eligible for Variable Compensation Plan

Commensurate with relevant qualifications and experience

Benefits:

Medical, Dental, and Vision Insurance

Health Savings Account

Flexible Spending Account

401(k) Retirement Plan with Company Match

Life and Disability Insurance

Critical Illness Insurance

Accident Insurance

Hospital Indemnity Insurance

Paid Time Off and Holidays

Flexible Working Schedule

Sphera is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

This job description is intended to convey information essential to understanding the scope of the job and the general nature and level of work performed by job holders within this job. This job description is not intended to be an exhaustive list of qualifications, skills, efforts, duties, responsibilities or working conditions associated with the position.

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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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.