Data Analyst

Nomo Fintech; London; On-site; GBP 40,000 - 70,000; Full time

Job summary

An established industry player is seeking a data analyst to join their dynamic team. This role offers the chance to work with complex datasets, collaborating across functions to deliver insights that drive business performance. You'll be at the forefront of promoting a data-driven culture, empowering teams with actionable insights and optimizing user experiences. If you thrive in a fast-paced environment and are eager to learn new technologies, this is an exciting opportunity to make a significant impact in the fintech sector.

Qualifications

• Minimum experience in financial services data analytics required.
• Proficiency with SQL, Tableau, R, and Python for data analysis.

Responsibilities

• Manage master data and ensure quality assurance for imported data.
• Analyze large datasets and translate findings into actionable strategies.

Skills

SQL

Tableau

Python

R

Data Analysis

Fraud Analysis

Data Visualization

Data Management

Tools

JIRA

Confluence

Excel

BI Tools

Mode

Athena

Job description

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 on identifying patterns of behaviour and ensuring methods of data ingestion, component rules, scenarios, and models are functioning as expected. You will analyze and report on data and metrics related to operations and mitigations, including building reporting dashboards used at the highest levels of the business and by external regulators. You will collaborate with stakeholders in each agile squad to provide insights and present findings to optimize performance, articulating these insights clearly and effectively to diverse audiences.

Responsibilities

1. Manage master data, including creation, updates, and deletion.
2. Manage users and user roles.
3. Provide quality assurance for imported data, working with QA analysts if necessary.
4. Commission and decommission data sets.
5. Process confidential data according to guidelines.
6. Handle data management and ownership: process varied data sources, recode, transform, merge, clean, and weight data to deliver clarity to clients. Own the data and understand it thoroughly.
7. Collaborate across functions: as the primary owner of collected data, work with multiple teams.
8. Analyze large, complex datasets and translate findings into strategies that inform decisions at all levels.
9. Drive continuous improvement by monitoring performance metrics and conducting analyses to identify optimization opportunities.
10. Promote a data-driven culture, empowering teams to leverage insights for rapid iteration and improved user experiences.
11. Identify and support process improvements to enhance efficiency.
12. Translate complex data insights into practical business strategies and communicate them clearly to diverse audiences.
13. Assess stakeholder requests strategically, prioritize based on value, and develop innovative data-driven solutions.
14. Apply strong data, reasoning, and analytical skills.

Skills and Experience

1. Minimum financial services-based data analytics experience.
2. Preferably experience in fraud, financial crime, or card payments domains.
3. Proficiency with SQL, Tableau, R, and Python for data analysis.
4. Comfort with querying relational databases and data lakes, handling data formats like CSV and JSON, and analyzing data using tools like Excel, BI tools, and basic Python scripts (Pandas, NumPy).
5. Experience working with large, unstructured datasets.
6. Eagerness to learn new technologies on the job.
7. Ability to simplify complex data insights for varied audiences.
8. Start-up attitude: comfortable in a rapidly changing environment, resourceful, self-starter, fast thinker, adaptable.
9. Knowledge of data tools like Mode and Athena is advantageous.
10. Experience with project management tools like JIRA and Confluence is desirable.
11. Experience with data visualization tools (Tableau, Looker, PowerBI) is a plus but not mandatory.