
Steyn Group · London
About ARMA: ARMA Jiu Jitsu Club is a new-to-market, premium Brazilian Jiu Jitsu gym in Clapham, London. The club is designed as a premier destination for BJJ t...
ARMA Jiu Jitsu Club is a new-to-market, premium Brazilian Jiu Jitsu gym in Clapham, London. The club is designed as a premier
destination for BJJ training, Personal Training, recovery, and productivity, bringing together high-performance sport and modern
lifestyle.
The Junior Content Creator is a fixed-term, part-time role based in London. The person in this role will support the creation of
digital content for social media, the website, and marketing campaigns, showcasing ARMA’s Personal Training and recovery
experiences. Day-to-day tasks include filming and editing short-form videos, capturing photos during classes and events, writing
captions and preparing content calendars in collaboration with the marketing team. The Junior Content Creator will assist in
managing social media channels, monitoring engagement, and responding to community interactions in line with brand guidelines. The
role also involves coordinating with coaches and staff to gather stories, updates, and promotions, and ensuring content is
delivered on time and reflects ARMA’s premium and community-driven brand.
Key Responsibilities
channels
contribute ideas to content strategy
delivery, and meeting content and campaign deadlines.
staff during busy training hours.
Experience
content.
The role We are looking to hire a Senior Analytics Engineer to join our Data Science team in London. This is a hybrid role based out of our London office. A minimum of 3 days per week in office is required. Working at WGSN Together, we create tomorrow A career with WGSN is fast-paced, exciting and full of opportunities to grow and develop. We're a team of consumer and design trend forecasters, content creators, designers, data analysts, advisory consultants and much more, united by a common goal: to create tomorrow. WGSN's trusted consumer and design forecasts power outstanding product design, enabling our customers to create a better future. Our services cover consumer insights, beauty, consumer tech, fashion, interiors, lifestyle, food and drink forecasting, data analytics and expert advisory. If you are an expert in your field, we want to hear from you. Role overview At WGSN, we believe that data is only as valuable as the decisions it empowers. As a Senior Analytics Engineer, you will sit at the vital intersection of Data Analysis and Data Engineering. Your mission is to bridge the gap between raw data and commercial value by building the internal tools, prototypes, and scalable data models that fuel our business intelligence. Unlike traditional data engineering roles focused on heavy production infrastructure, you will focus on agility—leveraging modern tech stacks and AI acceleration to spin up prototypes and methodologies quickly then scale dashboards and tools over time. As a Senior member of the team, you will be the champion of data best practices. You will initially focus on technical leadership as an individual contributor and mentoring other analysts to elevate their data modeling and software engineering skills. Over time, this role is expected to transition into direct line management responsibilities as the team expands. The team The WGSN Data team is a vibrant, multicultural mix of brilliant minds, blending global perspectives with deep expertise in retail and consumer analytics across a diverse range of industries such as fashion, beauty, interiors, and FMCG. Driven by a spirit of collaboration, we leverage our varied skill sets to transform complex datasets into high-impact insights, enabling our stakeholders to make confident, actionable, and results-driven business decisions. Key accountabilities Scalable Data Modeling: Design, build, and maintain robust, modular data models within Snowflake using dbt core, ensuring they are optimized for performance and aligned with business needs. Prototyping & Internal Tools: Rapidly build interactive GUIs, internal data applications and dashboards, and prototypes using Streamlit or similar to get actionable tools into the hands of stakeholders. Software Engineering Best Practices: Enforce modern software development standards across the analytics team, including rigorous version control (GitHub), CI/CD pipelines, and data testing paradigms. Data Integrity: Take ultimate ownership of data quality, cleaning, and transformation processes to ensure the wider business operates on a single source of truth. Team Mentorship: Actively coach and mentor data analysts, guiding them in writing production-grade SQL, adopting Python, and embracing dbt best practices. Culture of Learning: Foster an environment of continuous learning, specifically helping the team explore more advanced technologies. Translate Business to Tech: Partner with non-technical business leaders and technical engineering teams alike to translate complex commercial needs into working data solutions. Advocacy & Sharing: Proactively showcase new data products, share analytical insights with the wider business, and vocally champion data-driven decision-making in cross-functional meetings. Agile Execution: Manage your work and dependencies independently using JIRA within a sprint framework, remaining highly adaptable to changes in scope or project requirements. This list is not exhaustive and there may be other activities you are required to deliver. Skills, experience & qualifications required Data Warehousing: Advanced proficiency with Snowflake and writing highly efficient, complex SQL queries. Scripting & Modeling: Strong Python development skills for data manipulation and hands-on experience with data modeling (dbt core) UI/UX & Frontend: A proven track record of building user-friendly internal tools. A deep understanding of what makes a practical, intuitive UI/UX is what will set you apart. Experience with Streamlit is highly preferred (React is a plus). AI-Augmented Development: Comfort and experience using modern AI agents (e.g., VS Code, Cursor, Codex, or similar tools) to accelerate code generation, prototyping, and debugging. Advanced Data Tech: Exposure to or strong interest in data science concepts, machine learning workflows, vectorization/embeddings, and graph databases. Project Management: Comfortable working inside JIRA, managing sprints, and proactively calling out project dependencies. Empathetic Communicator: You are comfortable presenting to senior leadership one hour and debugging a query with a junior analyst the next. You know how to make technical concepts clear to anyone. 5-8 years of experience in Analytics Engineering or a combination of Data Analytics and Data Engineering required. The "Follow Your Nose" Mentality: You possess an analytical mind fueled by curiosity and resourcefulness. When data looks strange or an opportunity is hidden, you have the instinct to dig deep and simplify complex information.
OUR MISSION To become the car-changing destination of choice. By combining technology, media and deep automotive expertise, we've turned how people buy, sell, advertise and lease cars on its head. What started as a simple reviews site is now one of the largest online car-changing destinations in Europe. Last year alone we grew over 50% with nearly £3bn worth of cars bought on site, while £1.8bn of cars were listed for sale through our Sell My Car service. In 2024 we went big and acquired Autovia - creators of AutoExpress and Evo magazines - doubling our audience overnight. Together we now have one of the biggest YouTube channels in the world with almost 10m subscribers and over 1.1 billion annual views, while we sell 1.2 million print copies of our magazines and have an annual web content reach over 350million. And we’re a long way from done! THE ROLE We’re looking for a Senior Analytics Engineer / BI Analyst to bridge the gap between data engineering and business insight. You’ll take ownership of transforming raw data into trusted, well modelled datasets and deliver impactful reporting that drives decision making across the business. This role combines strong technical data modelling skills with stakeholder-facing analytics and BI development. WHAT YOU'LL BE DOING * Design, build, and maintain scalable data models using dbt on Google Cloud Platform (BigQuery) * Create and maintain dashboards and explores in Looker, enabling self-serve analytics * Translate business requirements into clear data models, metrics, and visualisations * Define and maintain core business metrics and data definitions in partnership with stakeholders and the wider analytics team * Implement data quality checks, testing, and documentation within dbt * Partner with stakeholders across all parts of the business including commercial, product, marketing, finance, and operations * Optimise query performance and manage cost efficiency in BigQuery * Mentor junior analysts and promote best practices in analytics engineering across the wider analytics team WHAT YOU'LL NEED * Previous experience in analytics engineering, BI or data analytics roles * Strong SQL skills (expert level, performance tuning experience preferred) * Experience working with modern cloud data platforms and distributed data warehouses (e.g. BigQuery, Snowflake) * Proven experience with dbt (modelling, testing, documentation) * Experience building dashboards in Looker (LookML is a strong plus) * Solid understanding of data modelling concepts (star schema, dimensional modelling) * Experience working with large-scale datasets * Strong communication skills with the ability to work with non-technical stakeholders NICE TO HAVE * Hands-on experience with Google Cloud Platform, especially BigQuery * Experience with orchestration tools (e.g. Airflow) * Knowledge of data governance and data quality frameworks * Exposure to reverse ETL tools (e.g. Hightouch) * Familiarity with AI coding assistants and a habit of integrating them into day-to-day analytics workflows SUCCESS IN THIS ROLE LOOKS LIKE * Clean, well-documented, and trusted data models used across the company * High adoption of Looker dashboards and self-serve analytics * Reduced time-to-insight for stakeholders with the use of AI tooling to accelerate delivery * Clear, consistent definitions of key business metrics * Improved data reliability and fewer reporting discrepancies WHAT YOU'LL OWN * The transformation layer (dbt) and semantic layer (Looker) * Core business metrics and reporting definitions * Data quality and testing frameworks * BI best practices and documentation standards WHAT’S IN IT FOR YOU * Hybrid working * Competitive salary to fund that dream holiday to Bali * Matched pension contributions for a peaceful retirement * Share options - when we thrive, so do you! * Vitality Private Healthcare, for peace of mind, plus eyecare vouchers * Life Assurance for (even more) peace of mind * Monthly coaching sessions with Spill - our mental wellbeing partner * Enhanced holiday package, plus Bank Holidays * 28 days annual leave * 1 day for your wedding * 1 day off when you move house - because moving is hard enough without work! * For your third year anniversary, get 30 days of annual leave per year * For your tenth year anniversary, get 35 days of annual leave per year * Option to buy 3 extra days of holiday per year * Work from abroad for a month * Inclusive parental, partner and shared parental leave, fertility treatment and pregnancy loss policies * Bubble childcare support and discounted nanny fees for little ones * The latest tech (Macbook or Surface) to power your gif-sending talents * Up to £500/€550 home office allowance for that massage chair you’ve been talking about * Generous learning and development budget to help you master your craft * Regular social events: tech lunches, coffee with the exec sessions, lunch 8 learns, book clubs, social events/anything else you pester us for * Refer a friend, get paid. Repeat for infinite money Diversity and inclusion is an integral part of our culture. We know that diverse teams are strong teams, so we welcome those with alternative identities, backgrounds, and experiences to apply for this position. We make recruiting decisions based on experience, skills and potential, so all our applicants are treated fairly and equally.
OUR MISSION To become the car-changing destination of choice. By combining technology, media and deep automotive expertise, we've turned how people buy, sell, advertise and lease cars on its head. What started as a simple reviews site is now one of the largest online car-changing destinations in Europe. Last year alone we grew over 50% with nearly £3bn worth of cars bought on site, while £1.8bn of cars were listed for sale through our Sell My Car service. In 2024 we went big and acquired Autovia - creators of AutoExpress and Evo magazines - doubling our audience overnight. Together we now have one of the biggest YouTube channels in the world with almost 10m subscribers and over 1.1 billion annual views, while we sell 1.2 million print copies of our magazines and have an annual web content reach over 350million. And we’re a long way from done! THE ROLE We're looking for a Senior Data Scientist to join our award-winning Data Science team at a pivotal moment. Carwow operates a two-sided marketplace — connecting car buyers and sellers at scale — and data science sits at the heart of how we make that marketplace smarter, faster, and more valuable for everyone in it. In fact, we recently won GenAI initiative of the Year at the British Data Awards. This is a hands-on, high-ownership role working centrally across the business. You'll partner with teams spanning Commercial, Marketing, Product, Finance, Engineering and Operations — developing and deploying ML and AI solutions that drive outcomes across both sides of our marketplace. The problems you'll work on are genuinely varied: pricing models, propensity and demand signals that sharpen marketing spend, personalised recommendations for our web product and CRM, and LLM-powered solutions for operational challenges like document verification. You'll translate ambiguous business problems into structured, production-ready solutions — and you'll be expected to deliver them end-to-end, from first principles through to being deployment-ready and beyond. WHAT YOU'LL BE DOING * End-to-End ML & AI Delivery: Lead data science initiatives from problem framing through to deployment, monitoring, and iteration — delivering the full production lifecycle. With no dedicated ML engineering function, you'll be responsible for ensuring your solutions are robust, scalable, and performing in the real world long after they ship. * GenAI & LLM Application: Design and build LLM-powered solutions where they create genuine business value — document processing, intelligent search, content understanding, and beyond. Apply them alongside classical ML with clear judgement about where each approach earns its place. * Commercial Impact: Connect your work directly to business outcomes. Whether you're building a model to improve marketing efficiency, a pricing signal to sharpen commercial decisions, or a recommendation engine to increase conversion — you understand the business lever you're pulling and design your solutions accordingly. * Prototyping & Experimentation: Move fast to test ideas before committing to full-scale development. Define rigorous success metrics upfront, validate honestly, and know when to double down and when to walk away. * Cross-Functional Partnership: Work closely with Commercial, Marketing, Product, Finance, Engineering and Operations stakeholders to understand problems deeply before reaching for a solution. Translate findings into clear, actionable narratives for both technical and non-technical audiences. * Standards & Craft: Contribute to shared best practices, documentation, and ways of working that raise the bar for the data science function — and help more junior team members grow alongside you. Drive continued adoption of AI capabilities to drive efficiencies, automation and constantly leverage new capabilities. WHAT YOU'LL NEED Please note: We know that no candidate will be the perfect match for all we've listed in this posting, so we’d encourage you to apply if you feel you're close to the brief but not an exact match. Ideally you’ll have * Commercial Mindset: You think about business impact first. You understand how your models connect to revenue, efficiency, or customer outcomes — and you use that to prioritise, scope, and communicate your work. * Stakeholder Partnership: Proven ability to work with commercial, marketing, and product stakeholders — translating business problems into well-scoped solutions and communicating technical solutions, challenges and outcomes clearly at all levels. * Sound Judgement: You navigate the tooling landscape with clear eyes — knowing when classical ML is right, when GenAI unlocks something new, and when a simpler solution is the more honest answer. Strong instincts for scalability, reliability, and explainability. * [Bonus] Marketplace or Two-Sided Platform Experience: Understanding of supply/demand dynamics and how data science creates leverage in a marketplace context. TEHCNICAL SKILLSET * Proven ML Experience: A strong track record of building, deploying, and maintaining ML models in Python in a production environment — not just notebooks. You've owned models after they ship and know how to keep them healthy. * Full-Lifecycle Delivery (MLOps): Comfortable delivering the end-to-end production lifecycle — model training, versioning, monitoring, and champion/challenger experimentation — without relying on a dedicated ML engineering team to carry that responsibility. * GenAI & LLM Expertise: Hands-on experience building LLM-powered solutions that deliver measurable business value. You understand how to apply, evaluate, and extend these tools — and you're honest about where they fall short. * Technical Depth: Solid experience in a cloud ML environment with software engineering principles — version control, code reviews, unit testing, and familiarity with containerisation. * Quantitative Rigour: Strong foundation in statistical evaluation and experiment design. You can define and defend success metrics, and you know when a model is degrading and what to do about it. * [Bonus] Experience with VertexAI TOOLS & TECHNOLOGIES * Languages: Python, SQL * Data & Transformation: dbt, Snowflake, BigQuery * Visualisation & BI: Looker * Engineering & MLOps: Docker, GitHub * Workflow & Orchestration: Vertex AI Pipelines (GCP), Kubeflow * LLMs & GenAI: Gemini API, Claude API INTERVIEW PROCESS * Step 1: People Team Screening Call (30 min) * Step 2: Hiring Manager Call: Experience (45 min) * Step 3: Technical Task: covering both Modelling & Production with Presentation (60 min + Task) * Step 4: Values Interview (45 min) WHAT’S IN IT FOR YOU * Hybrid working * Competitive salary to fund that dream holiday to Bali * Matched pension contributions for a peaceful retirement * Share options - when we thrive, so do you! * Vitality Private Healthcare, for peace of mind, plus eyecare vouchers * Life Assurance for (even more) peace of mind * Monthly coaching sessions with Spill - our mental wellbeing partner * Enhanced holiday package, plus Bank Holidays * 28 days annual leave * 1 day for your wedding * 1 day off when you move house - because moving is hard enough without work! * For your third year anniversary, get 30 days of annual leave per year * For your tenth year anniversary, get 35 days of annual leave per year * Option to buy 3 extra days of holiday per year * Work from abroad for a month * Inclusive parental, partner and shared parental leave, fertility treatment and pregnancy loss policies * Bubble childcare support and discounted nanny fees for little ones * The latest tech (Macbook or Surface) to power your gif-sending talents * Up to £500/€550 home office allowance for that massage chair you’ve been talking about * Generous learning and development budget to help you master your craft * Regular social events: tech lunches, coffee with the exec sessions, lunch 8 learns, book clubs, social events/anything else you pester us for * Refer a friend, get paid. Repeat for infinite money Diversity and inclusion is an integral part of our culture. We know that diverse teams are strong teams, so we welcome those with alternative identities, backgrounds, and experiences to apply for this position. We make recruiting decisions based on experience, skills and potential, so all our applicants are treated fairly and equally.