Junior Analytics Developer

In the ever-evolving digital landscape, data volumes are escalating, presenting both challenges and opportunities. We've reviewed the team and identified one of the challenges to be that we have insufficient resources to meet business demand. This is and area in great demand across the business and we need to support those needs.

It is expected that employing this additional junior resource the insight and analytics team will support with enhancing the decision-making, fuelling innovation and driving competitive advantage by extracting insight from vast data sets. Improving predictive analytics and optimising processes.

Job Accountabilities

• Work with business teams to identify requirements and understand where analytic insight can add value


• Develop a technical understanding and knowledge of key infrastructure and analytics tools


• Contribute to the development of analytical models and visualisations, based on functional designs and user requirements, to support strategic and operational decision making


• Select the most appropriate data analysis tools and techniques, including open source, some of which must be learnt quickly, as and when required


• Follow best coding practices and adhere to a suitable software development life cycle (SDLC) for the continuous development and implementation of analytic models ensuring performance, security and reliability are fully considered during the lifecycle


• Ensure compliance to relevant corporate policies regarding data security and processing


• Adhere to ethics framework for data analytics.

Communicate findings via data visualisation to a range of technical and non-technical audiences

• Work in an open, transparent and collaborative manner, sharing good practice and seeking to continuously improve the quality of outputs.

Contribute to the development of services that are automated, reliable and secure

• Work closely with data architects, data engineers, data managers, data owners and data developers


• Recommend and implement ways to improve data efficiency performance and reliability.
  
  Strong numeric, analytic skills and problem solving skills


• Knowledge of advanced analytical techniques (Statistics, Machine Learning, Deep Learning) and a demonstrable ability to evaluate and select the right approach for the nature of the problem to be solved


• Knowledge of multiple relevant technologies such as Relational databases, No SQL databases and Data Visualisation tools


• Demonstrable working knowledge of one or more relevant languages such as Python and SQL


• Experience of collecting, parsing, cleansing and analysing large data sets


• Good team working skills


• Ability to communicate with technical and non-technical audiences verbally and in written correspondence


• Demonstrates ability to learn, embrace challenges and be resourceful