Lead Data Scientist
- First data scientist at a funded London startup (two founders with proven track record)
- Build ML systems that predict future mobile app conversions weeks in advance
- Own the entire ML stack with direct business impact
- Design and implement end-to-end ML pipelines from data ingestion through model deployment and signal delivery
- Transform client-specific Jupyter notebooks into modular, config-driven pipelines using orchestration tools such as Prefect/Airflow
- Build robust API connectors handling schema evolution, incremental updates, and data quality validation
- Implement comprehensive machine learning model evaluation frameworks blending technical metrics (precision, recall, PRAUC, probability calibration) with business outcomes
- Develop AutoML capabilities optimised for time-series behavioural data and subscription lifecycles
- Implement sophisticated feature engineering for event-based data
- Design multi-model systems handling various prediction horizons and conversion definitions
- Optimise hyperparameter tuning using frameworks like Optuna, AutoGluon, or H2O
- Establish MLOps practices appropriate for a small team: experiment tracking, model registry, and monitoring
- Collaborate with engineering on CI/CD pipelines, testing frameworks, and deployment automation
- Implement data quality monitoring and model drift detection systems
- Design for scalability: from a dozen customers today to 100+ within 12 months
- Partner with the CTO on technical strategy and architecture decisions
- Work directly with client technical teams to understand data nuances and maximise predictive value
- Mentor junior data scientists through code review and pairing as the team grows
- Co-create OKRs and a technical roadmap with the founding team
- 5-8+ years building production ML systems with demonstrable business impact
- Strong experience with time-series analysis and behavioural event modelling
- Deep expertise in Python with high code quality standards
- Experience with modern ML stack (e.g. pandas/polars, sklearn, xgboost, PyTorch/TensorFlow)
- Proven track record delivering end-to-end ML pipelines: ingestion → feature engineering → training → deployment → monitoring
- Hands-on experience with cloud data warehouses (e.g. BigQuery, Snowflake)
- Track record of building automated, scalable systems from initial prototypes
- Right to Work in the UK (we cannot sponsor visas)
- Ability to work from Central London office 3 days/week (we believe in-person collaboration is crucial at this early stage)
- AutoML framework experience (e.g. AutoGluon, TPOT, Optuna, H2O.ai)
- MLOps tooling (e.g. MLflow, Weights & Biases, Evidently)
- Hands-on experience with orchestration tools (e.g. Prefect, Airflow, Dagster)
- Building robust API/ETL connectors with retry logic and incremental loading
- Statistical depth beyond standard metrics: calibration, cost-sensitive learning, causal inference
- Passionate about leveraging the latest LLM tooling for accelerated AI-enhanced delivery without compromising on quality
- Marketing attribution and conversion modelling
- Mobile app analytics and user lifecycle prediction
- Ad-tech ecosystem and privacy regulations (ATT, GDPR)
- Subscription business metrics and retention modelling
- Application Review: We will look through your application (CV, screening questions, and code samples) to see if you meet the initial requirements for this role.
- Initial Screen (20 mins with CTO): Short video call to assess mutual fit and technical background.
- Practical Exercise (take home, up to 2 hours): We'll book you in for a 2-hour slot at any time. You will be given a real-world modelling challenge that mirrors our work at Day30. Use any tools you'd use on the job (including LLMs, Copilot, etc) - we care about approach and outcomes, not memorisation.
- Technical Deep-Dive (60 mins, in-person): We will walk through your solution, discuss design and architecture decisions, consider alternative approaches, and work through live problem solving on solution extensions.
- Founder Conversation (30 mins): Meet both founders for us to understand your motivations and career goals, and for you to ask questions. We want to know that you'll be a great fit for our team, but we also want to help you achieve your goals too.
Compensation & Benefits
- Base Salary: Up to £95,000 per annum (depending on experience)
- Equity: Meaningful options as first technical hire
- Holidays: 25 days of annual paid leave, plus bank holidays.
- Flexibility: 3 days/week in Central London office, remote otherwise
- Equipment: Top-spec MacBook Pro and any tools you need
- Learning Budget: Conferences, courses, and resources to stay current
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