Data and Analytics

A data analyst collects, organises, and examines data to provide businesses with valuable data-driven insights. They use various data analysis and visualization tools, including business intelligence software, to locate, obtain, and transfer data between different systems and manage and refine the data to create comprehensive datasets. This data then sets trends and patterns to influence business decisions.

A Business Intelligence Analyst collects, analyses, and presents data to support business decisions. They collaborate with various stakeholders and are responsible for ensuring the data is stored and maintained properly in the company's database. This includes establishing procedures for utilising the database, providing technical support, and performing regular updates to ensure the data is accurate and up-to-date. BI Analysts also prepare analytical reports and make recommendations to stakeholders to make data-driven decisions that support growth and success.

Data scientists specialise in using data to solve business problems. They are responsible for collecting, managing, and analysing data from various sources to develop models and use statistical software to manipulate and visualise data to uncover insights and patterns. They build complex mathematical and analytical models using algorithms and machine learning techniques to create predictive models and make recommendations to guide investment and scale-up decisions.

Working in-house with organisations and in a consultancy capacity, customer relationship management analysts are responsible for analysing consumer, market and competitor data to design and develop strategic customer service initiatives. They help their employers or clients to benefit from data-driven decision-making around building brand loyalty and retaining customers.

A data engineer's role involves creating and building data products and services, and integrating them into business processes and systems. Their responsibility includes designing and sustaining the infrastructure that enables data scientists and analysts to handle massive amounts of data. They participate in creating and maintaining data pipelines, databases, and other storage solutions and develop business intelligence reports to establish accessible data for analysis.

ML engineers collaborate with data scientists to construct and deploy machine learning models, ensuring they are integrated and functioning efficiently in production environments. Their expertise in researching, building, and designing self-operating AI systems automates predictive models. ML engineers develop and design AI algorithms that can learn and make predictions, defining machine learning. Typically, an ML engineer works in a data science team, communicating with administrators, data analysts, data engineers, and architects. They act as a liaison between data scientists focused on statistical and model-building work and the construction of machine learning and AI systems.