Senior Data Scientist

Senior Data Scientist About ENSEK ENSEK builds the cloud‑native SaaS software that’s transforming how energy retailers operate, innovate and manage at scale. We help retailers lower operating costs, improve billing accuracy for consumers, and enhance customer experience through automation and AI‑driven insight, all underpinned by modern, cloud‑native architecture. ENSEK is at an exciting inflection point as we scale at pace towards new international horizons. If you’re driven by solving complex, real‑world problems and want to build modern technology that accelerates the global energy transition, you’ll feel right at home with us. About the role We are seeking a capable and proactive Data Scientist to join our Data Function. You will work closely with Product, Engineering and Commercial teams to translate business problems into clear data science opportunities that support decision-making and drive product and customer outcomes. You will own and deliver end-to-end data science solutions for complex use cases, which will include model development, deployment, experimentation and exploratory analyses. You will be comfortable working with large datasets and modern data science tooling, and will take ownership for ensuring solutions are robust, testable, and aligned to stakeholder and business needs. You will partner closely with cross-functional teams to shape problems, evaluate trade-offs, and ensure data science work delivers measurable value. You should be comfortable working with a high level of autonomy in ambiguity, balancing short-term delivery with longer-term thinking, and proactively identifying opportunities where data science can improve products, processes, or customer outcomes. This role is ideal for someone who combines strong technical foundations with excellent communication, stakeholder management and own building impactful, production-oriented data science capabilities. Key responsibilities: • Translate complex business problems into clear data science questions with measurable success criteria and expected business outcomes. • Own and design practical ML solutions, using experimentation to assess trade offs and challenge assumptions while balancing model performance, explainability, and usability. • Design robust data structures and features for modelling, accounting for system constraints and dependencies to ensure data supports reliable, scalable, and effective model behaviour. • Design experiments to evaluate model performance. • Validate model and analytical outputs and clearly communicate assumptions, uncertainty, and limitations to ensure accuracy and trust. • Write maintainable and robust production-quality SQL and Python code following best practices. • Understand the full model lifecycle in production and design appropriate monitoring, validation, and retraining approaches to ensure models remain reliable, robust, and effective over time. • Communicate findings, recommendations, and technical concepts in practical, accessible terms to both technical and non-technical audiences. • Follow data governance, security, responsible AI, and compliance standards when handling sensitive data, designing and deploying models. • Mentor junior team members and foster a collaborative environment through constructive discussion, documentation and knowledge sharing. • Contribute to improving team practices, modelling and engineering standards to strengthen data science capability across the organisation. Experience required: • 5+ years experience in a Data Science or Machine Learning role with a proven ability to identify and deliver end-to-end data-science solutions. • Strong analytical thinking and problem framing skills, with the ability to work independently to translate ambiguous business challenges into structured data science approaches. • Strong understanding of statistical concepts, experimentation, model selection, evaluation, and performance measurement, with proven ability to apply them appropriately in practical settings. • Experience working with a variety of AI/ML use cases, deploying and monitoring AI/ML solutions. • Strong proficiency in SQL, Python and data science toolkits (e.g. PyTorch). • Experience writing production quality code, with sufficient testing. • Experience working with Cloud Platforms and BI tooling. • Experience with Databricks and Sigma are desirable. • Ability to communicate findings and recommendations clearly to both technical and non-technical audiences • Strong attention to detail and commitment to building robust, reliable, and reproducible solutions with appropriate validation and documentation. • Energy industry experience is desirable Company Benefits 25 days’ holiday + bank holidays Option to buy or sell 5 extra annual leave days per year Vitality Health Insurance, including private healthcare, virtual GP access, mental‑health support and wellbeing perks (50% off gym memberships -Virgin Active, Nuffield, PureGym) Pension with 5% matched contribution Regular team‑wide and company‑wide events 2 volunteering days per year to give back Remote‑first working environment with offices in London and Nottingham Department Technology - Data & Reporting Locations United Kingdom Remote status Hybrid