Senior Applied Data Scientist / ML Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Identify and articulate ambiguous customer issues to ascertain if machine learning is the suitable solution.

• Acquire knowledge of and model customer operational environments, including routes, crews, and service histories.

• Develop necessary data and features utilizing Snowflake and dbt.

• Determine the delivery method for predictions to ensure customers comprehend, trust, and act on them.

• Communicate the realized impact to the Product team and the business using quantifiable outcomes.

• Establish evaluation criteria for model quality, drift, and reliability, both offline and online.

• Create A/B tests or causal analyses to validate improvements in customer results.

• Deploy, test, version, monitor, and identify drift in models.

• Collaborate with Product Managers and Software Engineers to integrate ML into product workflows.

• Set goals and direction for coding-agent-assisted development, critically assess outputs, and develop verification harnesses, backtests, evaluation scaffolding, and data validation checks.

⛳️ Requirements

• Over 5 years of experience in applied data science, ML engineering, or data engineering, with a focus on managing models in production.

• Proven track record of building and deploying at least one model into a real product.

• Proficiency in Python and applied ML libraries for tabular data, including scikit-learn, XGBoost or LightGBM, statsmodels or Prophet.

• Strong SQL skills.

• In-depth understanding of supervised learning, forecasting, ranking, recommendation, or optimization techniques.

• Experience in modeling complex operational data.

• Familiarity with dbt and Snowflake for modeling, feature pipelines, deployment, monitoring, and drift detection.

• Knowledge of AWS.

• Experience in measuring the business impact of a deployed model, including adoption, outcomes, or ROI.

• Excellent communication abilities, capable of explaining intricate technical trade-offs to product, engineering, and non-technical business stakeholders.

• Candidates must currently possess the legal right to work in the UK.

• Experience in B2B SaaS is a significant advantage.

• Bonus qualifications include experience with coding agents, decision intelligence, forecasting, customer behavior modeling, workforce/route optimization, operational intelligence products, senior or lead technical direction, or LLM/agentic workflows.

🏝️ Benefits

• Competitive company pension scheme with employer matching contributions.

• Generous holiday allowance with flexible time off plus UK bank holidays.

• Enhanced maternity, paternity, and parental leave policies.

• Continuous learning resources available.

• Comprehensive Employee Assistance Programme (EAP) offering free 24/7 mental health, legal, and financial support.

• Flexible working options available.