Data Scientist

Job Description

Data Scientist (Competitive salary: plus, bonus, enhanced benefits – including unlimited paid annual leave, discounted gym membership and more)

Profusion is a leading customer and business analytics agency, who work with companies large and small to use the power of AI to solve their business challenges. We specialise in data strategy, predictive modelling and email marketing, and provide a full suite of services for our clients ranging from consultancy advice, through to the creation and execution of data driven innovation projects and marketing campaigns. Our partnerships with universities and leading research organisations enable us to bring the best academic thinking and innovation into the solutions we offer our clients.

The key responsibilities of a data scientist are to take a scientific, data driven approach to solves business challenges and discover along the way not just the answer to the original questions asked, but also what new questions might be fruitful to ask. From a practical point of view, this may involve wrangling data from different sources into shape so that mathematical, statistical and machine learning methods can be applied to address the business challenge at hand. In other words, the data scientist’s primary focus will be in applying statistics and machine learning to help business stakeholders make smarter, better informed decisions. The data scientist will need to work closely with our clients to identify issues and use data and algorithms to propose solutions. Coding solutions that are replicable and clear to follow which will enhance the team’s productivity and results. The data scientist should also be able to engage in business storytelling to communicate his / her ideas in a clear and engaging way to non-technical business stakeholders.

Key responsibilities

Writing SQL queries to get the relevant data
Using Python or R to analyse data
Using Sisense to visualise data insights
Occasionally using Excel for some quick data analysis
Explaining to non-technical stakeholders the outcomes of the data analysis
Working with clients to research and innovate new ideas and concepts to solve new business challenges
Cleaning, exploring and aiding in the data analysis for ad-hoc projects.
Analysing, summarising and drawing insights from data in order to deliver BAU reports
Aid in developing and delivering data science training modules
Automating recurring data analysis reports
Designing a mathematical model to solve a business question
Translating a mathematical solution back into business language
Develop new ideas and support on innovation