Data Scientist working with data analytics to drive efficiency improvements in the energy sector. Collaborate with teams to build and deploy models for actionable insights.
About the role
- Data Scientist driving data-informed decision-making and building data models in AI product initiatives. Collaborating across teams to deploy scalable data solutions utilizing ML and data engineering.
Responsibilities
- Design, build, and deploy advanced data models, algorithms, and analytical frameworks to support AI and product initiatives.
- Collect, process, and analyse large structured and unstructured datasets to generate actionable insights.
- Apply statistical modelling, machine learning, and data mining techniques to solve complex business problems.
- Collaborate with cross-functional teams to identify opportunities for leveraging data to drive business solutions.
- Build scalable data pipelines and integrate analytical models into production environments.
- Develop and maintain dashboards, visualisations, and reporting systems to track model performance and business metrics.
- Contribute to experimentation strategies and design A/B testing frameworks for model and product evaluation.
- Stay current with advancements in data science, ML, and AI technologies, and proactively apply new methods and tools.
- Ensure data quality, governance, and compliance standards are upheld in all modelling and analysis work.
- Provide technical guidance and mentorship to junior data scientists and analysts.
Requirements
- Master's or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- 5+ years of hands-on experience in data science or applied machine learning.
- Proficiency in Python and data science libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow or PyTorch.
- Experience with building and deploying predictive models, experimentation frameworks, and statistical analyses.
- Strong knowledge of feature engineering, model evaluation, and optimisation techniques.
- Proficiency in SQL and experience with data warehouse technologies.
- Experience working with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Ability to communicate complex analytical concepts to non-technical stakeholders.
- Strong problem-solving and critical thinking skills.
- Experience in building data pipelines and working with modern data engineering tools.
Job title
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