Job description
Data Scientist, London, Permanent
Help us to develop Pay.UK's data science, machine learning, AI and predictive analytics capability by building robust predictive and forecasting models. This is a great opportunity to get stuck in and really take data analysis to the next level. You will also..
- Provide quantitative analysis in support of Pay.UK strategy and development initiatives.
- Use advanced data science techniques to identify trends, patterns and discrepancies in data and determine and direct gathering of additional data needed to support insights.
- Manage the development of strategic insight and research to support the payment ecosystem end to end and manage the distribution of published material, leveraging commercial opportunities as appropriate.
- Maintain understanding of the end-to-end payments landscape combining insights and data internally across Pay.UK, stakeholder engagement and horizon scanning of the industry leveraging from internal and external market analytics capabilities.
- Facilitate the transparency of the ecosystem to the supplier market, and provide insight that will support the mitigation of fraud.
- Apply data strategy including maintaining associated Data Policies that enable Pay.UK strategy and ecosystem needs (GDPR), and drive commercial opportunities that may arise from data exploitation.
- Use data modelling techniques to analyse market scenarios and communicate recommendations to business
Key Accountabilities
- Work with Big Data technologies to shape the development of analytical insight delivery.
- Use statistical data approaches to uncover patterns in data from which predictive models can be developed.
- Identify valuable data sources and automate collection processes.
Apply statistical techniques on large datasets to:
- Measure results and identify key underlying trends
- Build hypothesis and test significance
- Identify predictive indicators and causal impact and attribution
- Build predictive models to identify the likelihood of fraud
- Analyse geo-demographic and socio-economic profiling data along with transactional and behavioural data to produce critical insights and business deliverables
- Actively review market movements and industry research for insight on market dynamics, evolution of infrastructure and changes in payments sector
- Present findings to key stakeholders, and input to conversations on strategies to drive performance across the business
- Collaborate with colleagues and stakeholders to build data and analytical products that enable others to work with reporting effectively and making informed decisions that solve real business problems
- Maintain best-practice standards relating to data science techniques, coding and analytics
- Apply data science methods including regression (linear, logistic, multiple, multivariate), decision trees, segmentation and experimentation to drive opportunities and business decisions.
- Manage all aspects of data science project lifecycle and deliver within planned timelines
- Maintain industry recognised best practice including ML algorithm selection, propensity modelling, documentation, quality assurance, data governance and data privacy policies
Qualification, Skills & Experience
- Degree in a STEM subject or equivalent experience
- Professional experience applying data science and statistical methods with real data problems
- Expert knowledge in coding using Python or R
- Significant exposure in a Data Science and business intelligence technology stack (anaconda, Jupyter NB, databricks, R studio)
- Good knowledge and experience working with visualisation tools. e.g. Power BI, Tableau, etc
- Good knowledge and experience using SLQ and working with databases, including design, modelling and architecture e.g. SSMS, SSAS, SSRS and SSIS
- Good understanding of the Financial Services / Retail Payments market
- Strong experience with building predictive models and applying advance statistical forecasting
- Use statistical data approaches to uncover patterns in data from which predictive models can be developed.
- Experience with Cloud environments beneficial.
- Experience using a variety of data science tools, and selecting the right approach for the type of data or problem
- Professional qualification preferred but not essential
- Good understanding of Econometrics and how macroeconomic events can impact population, economy and ultimately the payments sector
- Strong skills in building predictive models to identify business opportunities and support informed decision making
- Experience using a variety of data science tools, and selecting the right approach for the type of data or problem
- Excellent stakeholder management skills coupled with the ability to quickly understand stakeholder needs and define and ensure the implementation of corresponding actions
- Ability to find innovative solutions to solve business problems and demonstrate intellectual curiosity and always strive to learn
- Build dashboards to visualise modelling outputs using visualisation tools such as Power BI and other tools suitable for disseminating agent-based simulation outputs
About Us
Pay.UK maintains and develops the UK retail payment systems and standards that are core to the economy being able to function on a day-to-day basis.
From Bacs to Faster Payments and cheques – we act as the single operator for all UK retail payments. We put the needs of consumers and businesses at the heart of everything we do, working in the public interest to ensure that the systems the country relies on for its banking transactions are safe, open, innovative and resilient.
Our payment systems underpin the services that enable funds to be transferred between people and institutions. In 2018, the UK's retail payment systems processed 8.8 billion transactions worth £7 trillion through Bacs Direct Credit, Direct Debit, Faster Payments, and cheques.
Every day, individuals and businesses use the services we provide to get their salaries, pay their bills and make online and mobile banking payments. Our vision for the future is to enable a vibrant economy, with Pay.UK delivering the best-in-class payment infrastructure and standards for the benefit of consumers and businesses nationwide.
Benefits Include
- 12% Non-contributory pension
- Discretionary annual bonus
- 30 days annual leave (excluding bank holidays)
- Private medical insurance, life assurance, income protection, health cash plan, dental insurance, Bupa medicals etc
- Employee assistance programme
- Cycle to Work Scheme
- Season ticket loan
- Annual fitness subsidy of up to £500 per annum