Customer Success Manager

Southwark
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst - Revenue/Sales

Data Analyst - Sales Operations

Data Analytics Lead - 12 Month FTC

Data Engineer

Senior Data Quality Analyst

Sustainability Data Analyst

A Client Relationship Manager is required in London to support B2B SaaS clients across the energy and housing sectors. This hybrid role focuses on building strong relationships with housing associations, councils, and energy service providers. The successful candidate will manage onboarding, support subscription use, and coordinate across internal teams to meet client needs. The position combines elements of customer success, client support, and account management, with a focus on delivering value and reducing client churn. Strong communication, problem-solving, and organisational skills are essential for success in this role.
 
Key Responsibilities

Manage relationships with key SaaS clients through regular meetings and calls.
Act as the main point of contact and advocate for client needs across internal teams.
Lead client onboarding and ensure contracts and purchase orders are in place.
Resolve client queries and escalations efficiently.
Support clients in using the platform effectively to reduce churn.
Coordinate with Sales, Product, Support, Finance, and Delivery teams.
Monitor and manage recurring revenue and invoicing processes.
Identify improvements to internal processes and use tools to increase efficiency.  
 
Experience & Skills Required

Previous experience working with B2B clients.
Background in Software as a Service (SaaS).
Strong organisational and task management skills.
Confident working across departments and delivering through others.
Excellent verbal and written communication abilities.
Skilled in problem resolution and handling escalations.
Proactive and comfortable working independently.
Experience in low-carbon energy, housing, or utilities (desirable).
Familiarity with IoT, data analytics, or wireless networks (desirable).
Capable of delivering client training on SaaS products (desirable).
Understanding of GDPR and information security (desirable).
Intermediate spreadsheet skills (desirable).  
 
What’s on Offer
This role offers an exciting chance to join a forward-thinking organisation driving change in the energy sector.  This hybrid role offers flexible working arrangements, with two days a week in the London office. Benefits include private medical insurance, 25 days holiday plus bank holidays, a generous pension contribution, and the option to work from anywhere for four weeks a year. Employees also receive a personal development budget, regular social events, and additional leave with tenure.

Salary:                  £40,000 - £50,000 Base Salary + 25 days hols + Bank Hols increasing with service, Private Health, Annual Personal Development Fund, Hybrid & flexible working, Work from anywhere in the world 4 weeks of the year, Quarterly company social, Quarterly team social, Cycle to work scheme.
Location:             London - Hybrid Working – 2 days per week in the office.
Company:           A forward-thinking SaaS business supporting energy and housing clients through smart technology and carbon reduction initiatives.

Diversity & Inclusion
Reymas Group operate an inclusive and diverse recruitment process, whilst also ensuring our clients do the same and we can provide any advice or education to them in relation to this. If there may be any support or adjustments required at any point throughout your recruitment journey with us, then please let us know and our trained consultants will assist and advise you accordingly

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 Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.