Data Analyst
London, United Kingdom
Data /
Full-time /
Hybrid
Who we are
BB2 Digital and Technology Services Ltd (t/a Nomo Fintech) is a cloud-based business-to-business Fintech company which owns the digital platform that powers the digital retail banking services of Bank of London and The Middle East plc (“BLME”), branded Nomo (available on iOS and Android), and provides various other services to BLME.
Nomo Fintech is currently in scale-up mode to support international digital banking across the GCC, and it’s an incredibly exciting time to join the business with great ambition and an effective combination of talent, culture, and world class technology.
Nomo Fintech leverages the support services of an intragroup entity based in Dubai which houses various functions to support Nomo Fintech’s business services.
Role Description
The data analyst will join the team to work to identify patterns of behaviour and ensure methods of data ingestion process, component rules, scenarios, and models are working as expected. In addition to this you will analyse and report on data and metrics relating to operations and mitigations. This includes building reporting dashboards that are used at the highest levels of the business and by external regulators. Working with stakeholders in each agile squad to provide insights and present findings to optimise performance by articulating these findings to diverse audiences in a clear, effective manner.
Responsibilities
- As you will expect the support a growing business needs is broad, but we hope that the following gives you an idea of the main focus of your attention:
- Managing master data, including creation, updates, and deletion.
- Managing users and user roles.
- Provide quality assurance of imported data, working with quality assurance analyst if necessary.
- Commissioning and decommissioning of data sets.
- Processing confidential data and information according to guidelines.
- Data management and ownership: You'll be processing varied data sources including recoding/transforming data, merging and cleaning, weighting etc. to enable us to deliver exceptional data clarity to our clients. You will need to ‘own’ the data and know it insideand-out.
- Cross-function collaboration: As the primary ‘owner’ of the valuable data we collect, you’ll need to collaborate with multiple teams.
- Dive into large, complex datasets and turn your findings into strategies that drive decisions at every company level.
- Drive continuous improvement initiatives by proactively monitoring performance metrics and conducting in-depth analyses to identify areas for optimisation.
- Champion a culture of data-driven decision-making, empowering teams to leverage insights from analytics to iterate rapidly and contribute to exceptional user experiences.
- Process improvements: Proactively identifying opportunities to improve efficiencies in these tasks and supporting the implementation of these improvements.
- Translate intricate data insights into practical business strategies and articulate these findings to diverse audiences in a clear, effective manner.
- Strategically assess stakeholder requests, prioritise based on value, and innovate datadriven solutions to enhance decision-making.
- Strong data, reasoning and analytical skills are essential.
Skills and Experience
- Will have at least minimum financial services based, data analytics experience.
- Preferably experience within the fraud and financial crime domain, or card payments.
- Key tools for Data Analytics understanding: SQL, Tableau, R, Python.
- You will be comfortable with data querying (relational databases and data lakes using SQL), data interchange (CSV, JSON etc), data analysis (such as Excel and BI tools, maybe even Access), data management and processing using at least simple Python scripts and notebooks (Pandas, NumPy etc).
- Will have experience working with multiple and large unstructured datasets.
- The adaptability and eagerness to learn new technologies on the job.
- You can simplify complex data insights for anyone to understand, whether they're tech-savvy or not.
- Start-up attitude – You’ll be comfortable in a rapidly changing environment, working with limited resources, and delivering high-quality work at the speed which is necessary for successful business growth. You’ll be a self-starter who doesn’t need much guidance, who can think fast on their feet and are ready to pivot when required.
- Familiarity with data tools like Mode, Athena is advantageous.
- Project and workstream management tools (e.g. JIRA and Confluence) is desirable.
- Data modelling with DBT is desirable.
- The more experience you have with data visualisation the better (but it's not a requirement of the role like Tableau, Looker, PowerBI and etc).
