Data.

Data Engineer A fast-growing AI technology company is looking for a Data Engineer to design, build and maintain scalable data pipelines supporting real-time products and data science initiatives. London-based hybrid role, with office attendance in Piccadilly 3 days/week.  Salary: £55,000–£60,000 + annual bonus and enhanced pension. Main Responsibilities: •    Build scalable and reliable ETL processes and data pipelines using multiple data sources.  •    Partner with data scientists to deploy models and analytics workflows into production.  •    Support the design and maintenance of the company’s data architecture.  •    Improve real-time systems, platform stability and ETL reliability.  •    Monitor and enhance data quality, performance and scalability.  Desired experience: •    Experience building scalable ETL processes and data pipelines.  •    Advanced Python for data processing. Candidates must be comfortable writing performant, production-grade code and clearly explaining it.  •    Experience with pandas, including transformations, joins, aggregations and large datasets.  •    SQL & Git.  •    Experience with cloud (Azure, AWS etc).  •    Ability to commute to the London office three days per week.  •    Experience with Airflow, Dagster, Jenkins, Tableau, Power BI, Synapse, Snowflake, Docker, RabbitMQ, Kafka or Spark would be advantageous, but is not mandatory.

An exciting opportunity for a Sr Data, Analytics and Martech leader to join a fast-growing online casino business at a foundational stage. This person will build the data function from scratch, creating the foundations for analytics, tracking, attribution, BI, customer insight and marketing technology. This is a hands-on leadership role for someone who understands both data analytics and digital marketing measurement. The business is currently migrating platforms and building its internal team, so they need someone who can define the strategy, but also get close to the data, vendors, tagging, attribution models and reporting setup. Main Responsibilities: Build and lead the data, analytics and marketing technology function. Create the data foundations, reporting framework and single source of truth for key business KPIs. Define tracking standards across web, app, CRM, paid media, affiliates and product journeys. Build a clear attribution and digital marketing measurement framework. Pull together data from platform providers, marketing channels and third-party tools such as paid social, search and CRM platforms. Support commercial, product, CRM and marketing teams with actionable analytics. Develop insight around customer behaviour, game performance, retention, churn, lifetime value and recommendations. Work closely with vendors and internal stakeholders to ensure data is structured, reliable and usable. Remain hands-on when needed, including extracting and analysing data using tools such as SQL, MySQL and/or Python. Desired experience: Data, analytics, BI, commercial analytics or marketing technology. Strong understanding of digital marketing, tracking, attribution and key marketing KPIs. Ability to work hands-on with data, not just advise from a management level. Strong knowledge of BI, reporting, data architecture, KPI frameworks and data governance. Understanding of CRM analytics, customer lifecycle, retention, churn and LTV. Strong stakeholder management skills and the ability to explain complex data topics clearly.    

Overview An opportunity to join a fast-growing, fully remote market maker focused on prediction markets. The business combines strong financial backing and industry expertise with the agility of a startup. The team is lean, highly technical, and focused on building high-performance trading systems through pragmatic engineering and rapid iteration. This is an opportunity to play a key role in shaping trading strategy, with direct ownership of performance, data, and execution. The Role This is a hands-on, live trading role overseeing highly automated strategies within sports prediction markets. You will be responsible for monitoring and improving real-time trading performance, identifying edge, and safely deploying strategy enhancements into production environments. The position is directly tied to live US sports markets and requires flexibility, including evenings and weekends, as part of a shared team rotation. Key Responsibilities Oversee live automated trading: Monitor real-time performance, exposure, and risk across markets during live sporting events, adjusting algorithmic parameters where required and intervening when necessary Improve trading strategy: Research, prototype, and validate pricing improvements, signal enhancements, and risk logic Own strategy rollout: Deploy updates through controlled methods, measure impact, and iterate based on performance Analyse trading data: Build and maintain reporting to track P&L attribution, fill quality, slippage, exposure, and model performance Backtesting & simulation: Validate all changes rigorously before applying to live markets Collaborate with engineering: Work closely with developers to translate strategy into production systems and improve trading infrastructure Contribute to product design: Apply trader insight to how markets are structured, priced, and settled Requirements Experience in sports betting, financial trading, or prediction markets Strong understanding of probability, expected value, and market dynamics Ability to work with data using Python and/or SQL Comfortable contributing to or working alongside production trading systems Quantitative background in Mathematics, Statistics, Computer Science, Engineering, Economics, or similar Experience analysing and interpreting large datasets Willingness to work flexible hours aligned with US sporting schedules (including evenings and weekends) Strong ownership mindset with the ability to operate in a fast-paced startup environment Curiosity and comfort working with AI tools to enhance research and analysis Domain Experience (One or More) Sportsbook or betting operator (trading, pricing, risk, or trading operations) Personal betting track record with demonstrable edge Financial markets or systematic trading background Nice to Have Experience with prediction markets or exchange-based products Sports modelling (e.g. in-play, player props, correlated markets) Machine learning applied to trading or pricing Experience building data pipelines, dashboards, or reporting tools Exposure to C#/.NET or similar trading system environments Experience operating automated strategies in production Why Apply? Shape trading strategy from an early stage Direct ownership of performance and P&L Work with a small, high-performing and technical team Backed by a leading iGaming organisation Fully remote with flexibility across US time zones Competitive compensation with equity upside