Data Scientist (225-724)

A Data Scientist is an analytical expert who utilises their skills in both technology and social science to find trends and manage data. They use industry knowledge, contextual understanding, and skepticism of existing assumptions – to uncover solutions to business challenges. This position requires a unique combination of skills in data analysis, statistical modelling, machine learning, and programming. As a Data Scientist, you'll be responsible for designing and implementing data-driven strategies to drive business growth and efficiency. You'll need to work closely with researchers, engineers, and other stakeholders to gather and process large datasets, and then apply complex algorithms to extract valuable insights. The role is integral to translating business needs into natural language processing, data visualisation, or predictive analysis tasks, this ultimately drives policy, strategic decision-making, and process improvements.

Responsibilities

• Identify valuable data sources and automate collection processes.
• Undertake preprocessing of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.
• Build predictive models and machine-learning algorithms to forecast outcomes.
• Combine models through ensemble modeling techniques to optimize results.
• Present data findings to both technical and non-technical stakeholders.
• Collaborate with engineering and product development teams collaboratively.
• Propose new data acquisition tools and techniques to enhance processes.
• Perform data validation to ensure data accuracy and integrity consistently.
• Research and apply new technologies to improve data processing efficiencies.
• Work closely with domain experts to understand their analytical needs.
• Develop processes and tools to monitor and analyze model performance effectively.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field required.
• Proven experience as a Data Scientist or Data Analyst in a relevant field.
• Strong proficiency in programming languages such as Python or R is essential.
• Familiarity with data visualisation tools like Tableau or PowerBI is necessary.
• Understanding of machine-learning techniques and algorithms is key.
• Excellent analytical and problem-solving skills for critical data analysis.
• Experience with SQL and database management for handling data queries.