Job description
We're building a data science team and we want an innovator who can shape what we do. We want someone who can bring enthusiasm, experience, creativity and brilliant data science skills.
There's all the usual company stuff about working with lots of interesting people but we'd rather get to the point, we have world class products which bring in fantastic data and now we want to put it all together and solve problems in customer experience and fraud prevention.
Core Responsibilities
- Develop, test and refine data models and algorithms to solve a wide variety of industry problems.
- Shape our tools and techniques which start us on the journey towards data science excellence.
- Work with stakeholders throughout the organisation to identify opportunities for leveraging data to drive business solutions.
- Analyse data to drive optimisation and improvement of our data platform products.
- Mentor, coach and build a world class data science capability in our business.
- Ad-hoc analysis of customer data, presenting the results in a clear and engaging manner.
- Keep current with technical and industry developments, coaching and teaching so we grow as an organisation.
Skills & Requirements
- Strong problem solving skills, probably 5+ years working with statistical models, and likely a background in statistics, mathematics or another quantitative field.
- Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.
- Experience analysing data from 3rd party providers is interesting but not essential (for example: Google Analytics, Experian, Equifax, Adwords, Facebook Insights, etc).