At a Glance
- Tasks: Join us to build innovative systems that enhance sales and marketing efficiency.
- Company: HowNow, a disruptive learning platform transforming how people upskill.
- Benefits: Competitive salary, hybrid work, flexible hours, and generous holiday allowance.
- Other info: Enjoy a vibrant workplace culture with monthly socials and a dog-friendly environment.
- Why this job: Be part of a dynamic team shaping the future of learning and technology.
- Qualifications: Experience in GTM engineering and familiarity with modern tech stacks required.
Our mission is to make meaningful learning a part of your everyday. The shelf life of our skills is now less than 5 years. So, if you stopped learning today, your skills would soon be irrelevant. Think that’s a big problem? You’d be right. Enter HowNow. Founded in 2019, our Learning and Skills Platform is disrupting the way people learn and upskill through technology. Whether it's finding a quick answer, learning skills or tapping into shared knowledge, we make it easy for people to learn what they need, when they need it.
Already used by fast-growing scale-ups and global enterprises, such as Trainline, Depop and Sanofi, we’re pushing the boundaries of how people learn.
The role is a new title for us, and a deliberately broad one. You'll own the systems that put the right accounts in front of the right people, ensure every lead is scored and routed properly, and eliminate the manual steps that slow Sales down. You'll also own HubSpot as our system of record and the reporting that tells us what's actually working. Where Marketing and Sales own the analysis and the calls it drives, you own the infrastructure and data that makes those calls possible.
Day-to-day tasks will include:
- Build our outbound growth engine
- Own list building and targeting: sourcing the right accounts and contacts before anything else gets sent
- Design and build automated outbound systems (sequencing, enrichment, AI personalisation) that make outbound feel 1:1 at volume
- Own the stack that powers it, and how it all connects into HubSpot
- Build the intent-driven lead conveyor belt (Project: No Lead Left Behind)
- Partner with Marketing to build the automated infrastructure that scores and routes every lead, inbound and outbound, by fit and intent
- Speed up the sales process
- Work closely with Sales to find the manual, repetitive steps slowing deals down, and fix them with automation, AI, or just a better process
- Own HubSpot and baseline reporting
- Keep HubSpot clean as the system of record, and make sure we can see what's working: pipeline, conversion, where deals stall
- Use that data to keep improving the system itself, not just report on it
- Partner with Marketing on attribution
- Own the GTM tech stack end-to-end
The key things that we will be looking for in applicants:
- Two or more years in GTM engineering, growth engineering, revenue operations, or outbound-heavy demand generation
- Hands-on with the modern GTM stack: enrichment and list building, sequencers, no-code automation, and HubSpot specifically
- Comfortable with APIs, spreadsheets, and SQL at depth, and light scripting
- You understand the difference between fit and intent, and you've built or worked with logic that scores and routes leads based on both
- You've owned a GTM tech stack end to end
- Comfortable partnering with Marketing and Sales rather than working around them
- Genuinely fluent in AI tools for GTM
What you’ll get:
- Base salary band for this role is £50-62K per annum, with a 10% discretionary bonus
- Hybrid working (2x a week in our London office, Tuesday/Wednesday and Thursdays) and flexible working hours
- Work from anywhere, for up to two weeks per quarter
- Wind-down Fridays: No meetings from 2pm onwards on Fridays
- Enhanced maternity and paternity policies
- 25 days holiday, plus bank holidays and your birthday day off
- An enhanced employee pension scheme
- Private health insurance through Bupa, plus access to Yulife
- An annual £500 learning and development budget
- Dog-friendly offices
- Monthly socials
- Access to the very best learning platform out there (HowNow+)
- Cycle to Work scheme
- Financial wellbeing support via Mintago
What's next?
Once you've applied, we'll get back in touch with you. This is usually within the next 3 working days. Sometimes it can take slightly longer, but we will get back to you as soon as we can, regardless of the outcome of your application.
- You'll be invited to a 45-minute video call with Pauline, our VP of People
- A 45-minute interview with Duncan, our Head of GTM
- A 1-hour, task-based interview with Duncan, Nelson, our CEO and Co-Founder, and Kuvera, our COO and Co-Founder
GTM Engineer - Hybrid (UK) in London employer: HowNow
HowNow is an exceptional employer that fosters a dynamic and inclusive work culture, perfect for those looking to thrive in the fast-paced SaaS industry. With competitive salaries, hybrid working options, and a strong emphasis on employee growth through learning budgets, we empower our team members to excel while enjoying a dog-friendly environment that promotes well-being and collaboration.
StudySmarter Expert Advice🤫
We think this is how you could land GTM Engineer - Hybrid (UK) in London
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like HowNow.
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We think you need these skills to ace GTM Engineer - Hybrid (UK) in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at HowNow, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at HowNow. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at HowNow
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at HowNow!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
