An opportunity exists for a new Data Scientist to help Atom enhance its data & analytics capability
Insight & Intelligence have responsibility for the management of Atom’s data from end to end, from sourcing and integration, right through to delivery of business reporting and predictive models.
Developing and implementing various types of predictive models, segmentation strategies, optimisation algorithms and data mining analysis including:
- Predictive models and analysis to drive pricing and liquidity management
- Supporting regulatory and compliance initiatives within risk such as IFRS9 & IRB models and stress testing
- Credit Risk scorecards
- Simulation models to help optimise operational processes and quantify and manage operational risks
- Delivering end-user solutions to enable customers to utilise predictive models to perform what-if analyses.
- Monitoring and maintaining models to ensure that they remain fit for purpose
- Providing peer review and challenge to analysis and models developed by other members of the team.
As part of the role there will be an opportunity to be involved in all parts of this life cycle within the wider team to support our dynamic business.
The role will give a rare opportunity to work with all functions within the bank, giving insight to a wide range of activities, working with external data and analytics suppliers where required. Furthermore, as the business grows, the requirements for analytics will expand significantly, providing opportunities to expand your own capabilities.
If you are an analytical expert and want to help build an analytics capability that will be the envy of other banks, then apply now!
- Delivering predictive models that generate significant uplift in business performance and/or provide an enhanced customer experience
- Delivering analysis to support key strategic projects
- Delivery of analysis to support regular reporting requirements
- Delivering ad hoc analysis to provide key insight into business performance
Key Performance Indicators
- Accuracy of information delivered
- Timeliness of work completed
- Technical programming and modelling ability
- Extent of contribution to team deliverables
- Alignment of activity to team goals
- Degree in a numerate discipline (e.g. Maths/Statistics/Economics or similar) with a high degree of statistics.
- Sound understanding of one or more of the following modelling techniques – collaborative filtering, support vector machines, neural networks, linear and logistic regression, decision trees, random forests
- Experience of data analysis tools, such as SQL, R, Python, SAS or similar
- Good working knowledge of MS Excel
- Good communication skills - able to present analysis at all levels of the business and to non-specialists
- A self-starter with excellence time management skills
- Data visualisation with tools such as Tableau, Shiny
- Experience of delivering predictive models to support application or behavioural credit risk scoring, IRB, IFRS9, scorecards, pricing and price elasticity, or product propensity models.
- Knowledge of Scala programming language.
- Awareness of streaming technologies such as Apache Kafka
- Delivering analysis and/or reporting in a Financial services environment,
- Experience in dealing with large data sets
The legal bit.
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