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The Data Scientist role involves collecting, cleaning, and transforming data, developing predictive models, and conducting exploratory data analysis. The role focuses on being a partner with business stakeholders to identify and prioritise opportunities where data science can deliver measurable value for our client, one of the UK’s major energy providers.
Job Responsibility:
Collect, clean, and transform structured and unstructured data from multiple internal and external sources
Develop, test, and deploy predictive models and machine learning algorithms to address business challenges
Conduct exploratory data analysis (EDA) to uncover trends, patterns, anomalies, and key drivers
Communicate insights and recommendations through clear storytelling, visualisations, and dashboards
Collaborate with engineering teams to productionise models and ensure reliability, scalability, and ongoing performance
Evaluate model accuracy and effectiveness, implementing continuous optimisation and tuning
Stay up to date with emerging data science tools, methodologies, and industry best practices
Perform sensitivity analysis to assess model robustness and variable impact
Requirements:
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline
Minimum 3-5 years’ experience in client-facing Data Science roles with demonstrable impact on business outcomes
Strong proficiency in Python or R, including libraries such as pandas, scikit-learn, NumPy, TensorFlow, or PyTorch
Solid understanding of statistical analysis, hypothesis testing, and experimental design
Hands-on experience applying a range of supervised and unsupervised machine learning techniques (e.g., Random Forest, regression models, clustering methods)
Proficiency with SQL and data warehousing technologies
Ability to translate complex analytical findings into clear, practical business recommendations
Strong problem-solving skills and natural curiosity for exploring and understanding data
Nice to have:
Experience working with cloud platforms such as Azure
Background in deploying machine learning models into production environments (MLOps experience is advantageous)
Hands-on experience with big-data or distributed computing tools such as Fabric
Familiarity with visualisation tools such as Power BI, Tableau, or Plotly
Industry experience primarily in Energy & Utilities
Excellent communication and data-storytelling capabilities
Effective collaboration and stakeholder-engagement skills
High attention to detail and commitment to data accuracy
Continuous learning mindset and openness to new techniques and technologies
What we offer:
Smooth integration and a supportive mentor
Pick your working style: choose from Remote, Hybrid or Office work opportunities
Projects have different working hours to suit your needs
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Individual coaching sessions or accredited Coaching School