Data Lead

Togather
London
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineering Lead - Cloud Pipelines & Governance

Sports Data Scientist

Sports Data Scientist

Data Engineer

Head of Data Engineering (Manchester/Hybrid, UK)

Head of Data Science

Togather started life as Feast It, in 2017, as a booking platform for people to book street food caterers for their birthday parties and weddings. Since then, we have grown to become the UK’s biggest events platform as Togather for food, drink, venues, photographers and so much more.

We’re here to help people make amazing memories on some of the biggest and best days of their lives. Whether they’re planning the whole-company summer party, hosting an epic dinner party, or running an entire festival, we can - and do - help with all of it.

None of this would be possible without our amazing community of partners, who we handpick from across the country.

We’ve worked with everyone from Amazon, Nike, and London Pride, to Tom Cruise, Star Wars, and Taylor Swift. Within the office, we recently came #7 in the Startups 100 Awards and have been named in the top 15 in Tempo's 50 Best Places To Work. Our team truly love and care about what they do, which makes working here that much easier.

The Role:

We are looking for a Data Lead or a Snr Data Analyst to lead our data strategy in the business. Our vision is that data informs the beginning and end of every decision that we make, and this means the role will work closely with all areas of the business to empower and elevate their decision making. In line with our squads model, this role will help explore big business questions such as modelling and forecasting, as well as contribute to the product discovery process and champion better insights and analytics.

You'll report to our Head of Product  but find yourself interacting with the wider senior management team. We're looking for someone who is independent, autonomous, passionate about showing what can be achieved with data and about creating a culture that encourages people to learn through.



Your responsibilities:

Own business as usual reporting & analysis:

  • Being a proactive consultant for our internal teams, deriving insights that can be used to improve performance
  • Working with commercial, product, growth and marketing teams to define their data analysis requirements & provide ongoing analysis
  • Creating and sharing compelling data-driven stories to audiences of varying analytical literacy
  • Developing our dashboarding within Looker to enable teams to self-serve their data requirements
  • Being a champion/leader for data in the organisation, and helping upskill internal team members
  • Data classification and analysis from 3rd parties as part of our Live events

Provide project teams with data insights:

  • Support project teams with data insights to focus on the highest impact changes, prioritise effectively and measure results
  • Working with senior management teams to plot key business strategic direction using data

Developing our data stack alongside our Engineering team:

  • Helping design, document and maintain data stack system processes
  • Working with our engineering team to improve any issues with our data stack and BI
    Tools
  • Collaborate with our engineering team to iterate and improve on our machine learning Matchmaking model
  • Work along with the team and business with ongoing A/B testing and analysis

Requirements

Ideally you will have a breadth of experience in extracting insights across many different data sources (e.g. relational databases, Google Analytics, Segment, Split.io), transforming data via DBT, and visualising those insights using a range of tools (e.g.

Looker, Google Sheets).

  • Experience in defining and creating metrics for consumption by our BI tool and other services
  • Experience using data visualisation tools. We use Looker and experience here will be a big bonus, but other tools & experiences are of course still relevant.
  • Adept at executing end-to-end analytics projects: gathering requirements, defining measures of success, validating data sources and analysis methods, delivering insights and presenting to stakeholders to ensure the key insights and recommendations are identified and delivered
  • Experience in analysing data to draw business-relevant conclusions and in data visualisation techniques and tools
  • Advanced SQL skills and experience transforming data with DBT
  • Excellent understanding of commercial KPIs with strong ability in storytelling, providing proactive as well as reactive insight.
  • Team player with strong interpersonal, relationship-building, and stakeholder management skills
  • Strong written and verbal communication skills including technical writing skills
  • Logical and creative thinking skills: you can approach a problem, applying logic and creativity
  • Data classification and analysis from 3rd parties as part of our Live events
  • You'll be the core of our data team, and  so you'll need comfortable and effective working independently

Benefits

Our offices are in London and we work with a hybrid model which requires a minimum of 3 days a week in the office.

We are passionate about equal opportunities and improving the tech industry for the better, so if you are from an underrepresented background then we would particularly love to hear from you.

  • Overtime / TOIL policy
  • Learning & Development budget (Health & Safety, CAD, Project Management, Sales & Partnerships…)
  • Team wellness and social budget
  • Partnership with Health Assured with EAP service
  • 25 days + Bank Holidays annual leave allowance
  • Hybrid working policy with a working from home budget (currently 3 days office, 2 days WFH)
  • Over & Above award (£100 restaurant voucher)
  • Partnership with Mintago - enhanced pension and financial support
  • Generous option awards
  • Cycle to work scheme
  • Invites and ticket to food and event industry events
  • Significant discounts at London’s best restaurants and bars
  • A great parental leave policy
  • We are a climate positive workforce through our partner Ecologi
  • A top of the range Macbook to work on

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.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.