As a Senior Data Scientist, you’ll guide an agile multifunctional team including a Junior Data Scientist, Domain Expert and a Data Engineer. Your role will be to apply your broad skillset across data and analytics to understand business problems, create insights and envisage practical solutions in areas such as trade processing and information technology.
Your broad area of responsibility will be to assist us defining and delivering a roadmap of data initiatives that identify efficiencies, unlock opportunities, and generate revenue. You will have access to large data sets, giving you the ability to make a tangible impact with your analysis. In return, you will be given support to expand your technical and domain skills.
As a Data Scientist, you’ll work directly with our business units to ideate, prioritise and perform the initial feasibility checks on ideas to improve business outcomes, leveraging data and prioritising these ideas through benefits modelling. By determining appropriate analytical approaches to solving business problems, you’ll identify whether these requirements can be achieved via existing internal or external capability or via engineering new solutions.
In addition, you will be responsible for:
- sourcing and identifying relevant data sources, cleaning and preparing data
- performing modelling and analysis using charting, descriptive statistics and machine learning
- creating impactful dashboards and consumable insights using human centred design principles
- communicating complex concepts simply and translating outputs into actionable insights for business stakeholders
- defining and providing requirements to data engineers in order to automate data
- mentoring junior data scientists including reviewing code and analysis approaches.
To be successful in this role you will have some of the following skills/background and experience:
- 5+ years experience in a hands-on data science role – you are considered an expert and have either led a team or mentored more junior team members
- curious and business outcome focused with a problem-solving attitude
- evidence of having innovated and improved a business outcome using data, rather than just implementing a requirement
- experience in delivering the full lifecycle of projects from R&D through to deployment
- strong collaboration skills having worked with business stakeholders to identify and shape problems to be solved with data
- accessed and sourced data from a variety of systems using SQL and APIs
- expertise in cleansing, combining and processing data
- comfortable using Python or R
- practical experience with machine learning and statistics
- familiarity with data visualization tools (e.g. Microstrategy, PowerBI, Tableau, Quicksight, Qlik)
- proficiency working with large data sets (10m+ records) and cloud computing would be an advantage.
Ideally, you will have commercial exposure in a corporate, consultancy or start-up environment, and a financial services background is an advantage.