Applied Data Scientist (Azure)

Sword is a leading provider of business technology solutions within the Energy, Public and Finance Sectors, driving transformational change within our clients.  We use proven technology, specialist teams and domain expertise to build solid technical foundations across platforms, data, and business applications.  We have a passion for using technology to solve business problems, working in partnership with our clients to help in achieving their goals. 

About the role:

At Sword, we partner with major energy organisations to deliver data-driven transformation at scale. We are now looking for a Data Scientist to join our team, supporting a high-profile engagement within the renewables sector.

You’ll work at the intersection of data, engineering and business insight — turning complex datasets into production-ready machine learning solutions that create measurable impact. This is not a proof-of-concept environment; your models will be deployed, monitored and continuously improved within a live Azure ecosystem.

You will collaborate closely with business stakeholders, data engineers and technical specialists to translate real-world energy challenges into intelligent, scalable solutions.

As a Data Scientist, you will:

• Conduct data cleaning, preparation and exploratory data analysis (EDA) to uncover actionable insights
• Communicate findings clearly using data visualisation tools and structured reporting
• Build, train and evaluate machine learning models using Python
• Use Azure Machine Learning to manage datasets, run experiments and deploy models
• Implement and maintain MLOps pipelines to automate model training, deployment and monitoring
• Work with stakeholders to translate business problems into data-driven solutions
• Present insights, model outputs and recommendations to both technical and non-technical audiences
• Contribute to best practice in model governance, reproducibility and performance optimisation

Requirements

• A degree (or equivalent practical experience) in Data Science, Computer Science, Mathematics, Statistics or a related discipline
• Experience working in a Data Scientist or similar analytical role
• Strong proficiency in Python and relevant data science libraries
• Hands-on experience with Azure Machine Learning
• Practical understanding of machine learning algorithms and model evaluation techniques
• Experience implementing or contributing to MLOps practices
• Strong data exploration and data visualisation skills (e.g. Power BI)
• Experience building, deploying and managing machine learning models in production environments

Desirable:

• Experience with Azure Databricks or Spark
• Familiarity with Azure Data Factory or other ETL tools

Benefits

At Sword, our core values and culture are based on caring about our people, investing in training and career development, and building inclusive teams where we are all encouraged to contribute to achieve success. We offer comprehensive benefits designed to support your professional development and enhance your overall quality of life. In addition to a Competitive Salary, here's what you can expect as part of our benefits package:

• Personalised Career Development: We create a development plan customised to your goals and aspirations, with a range of learning and development opportunities within a culture that encourages growth.
• Flexible working: Flexible work arrangements to support your work-life balance. We can’t promise to always be able to meet every request, however, are keen to discuss your individual preferences to make it work where we can.
• A Fantastic Benefits Package: This includes generous annual leave allowance, enhanced family friendly benefits, pension scheme, access to private health, well-being, and insurance schemes.

At Sword we are dedicated to fostering a diverse and inclusive workplace and are proud to be an equal opportunities employer, ensuring that all applicants receive fair and equal consideration for employment, regardless of whether they meet every requirement. If you don’t tick all the boxes but feel you have some of the relevant skills and experience we’re looking for, please do consider applying and highlight your transferable skills and experience. We embrace diversity in all its forms, valuing individuals regardless of age, disability, gender identity or reassignment, marital or civil partner status, pregnancy or maternity status, race, colour, nationality, ethnic or national origin, religion or belief, sex, or sexual orientation. Your perspective and potential are important to us.

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