At a Glance
- Tasks: Transform complex data into actionable insights and develop automated dashboards.
- Company: Join a leading organisation in the financial services sector with a focus on innovation.
- Benefits: Competitive salary, 10% bonus, hybrid work model, and opportunities for professional growth.
- Other info: Work in a collaborative team and advance your career in a fast-paced setting.
- Why this job: Make a real impact by driving data-driven decision-making in a dynamic environment.
- Qualifications: Experience in SQL, data analysis, and familiarity with regulatory frameworks required.
Role- Hybrid Senior Data Analyst – London – 3 days a week in the office
Looking for a hybrid Senior Data Analyst with active security clearance, (SC), based in London paying £75,000 to £80,000 + 10% bonus to drive supervisory effectiveness by transforming entity and regulatory data into actionable insights.
Embedded within a live testing programme for a new regulatory reporting regime, the role equips Supervision teams with the dashboards, analytical tools, and intelligence needed to identify risks, prioritise interventions, and monitor firms effectively.
Key Responsibilities & Impact
- Data Transformation: Translates complex regulatory data into high-impact insights and supervisory tools.
- Programme Testing: Ensures the robust delivery of the new reporting regime by leading systems acceptance, testing firm feasibility, and optimizing data usability for supervisors.
- Quality Assurance: Accelerates and deepens the testing process, delivering greater organizational confidence in the final regulatory data build.
- Key Responsibility
- Supervisory Outcomes: Analyse risk indicators, alerts, and insights to enable agile, risk-based supervision and data-driven decision-making.
- Regulatory
- Data
Integration: Synthesise complex datasets—including authorisations, holdings, transactions, and regulatory reporting—into cohesive, cross-firm views that replace fragmented data sources.
- Risk Analytics & Intelligence: Identify market trends, anomalies, concentrations, and emerging risks to drive thematic reviews, quantitative investigations, and alert triage.
- Data Quality & Enrichment: Implement robust validation controls and verify Legal Entity Identifiers (LEIs).
Enrich core datasets by integrating external sources like GLEIF, Companies House, and market proxies.
- Reporting & Automation: Build automated, self-service Tableau dashboards and management information (MI) to transition Supervision teams away from manual tracking.
- Stakeholder Engagement & BA: Facilitate workshops to gather requirements and translate complex supervisory challenges into clear analytical blueprints, alignment plans, and governance strategies.
- Future-State
Capability: Advance the organisation's analytics maturity by developing continuous monitoring tools, predictive early-warning indicators, and automated reporting frameworks.
Skills
- SQL and large-scale data analysis across complex, multi-source datasets.
- AWS services such as S3, Dynamo DB, Athena, etc.
- Data visualisation and dashboarding in Tableau or Power BI.
- Data quality assessment, validation and improvement.
- Stakeholder management across business and technical audiences.
- Regulatory or financial services experience.
- Familiarity with regulatory or financial data reporting regimes.
- Personal Skills
- Self-Driven Leadership: Highly proactive and self-directed; establishes strategic direction, maintains momentum, and delivers results with minimal supervision.
- Strategic Agility: Operates seamlessly across diverse business areas, rapidly absorbing domain knowledge and building cross-functional relationships.
- Adaptability: Pivots fluidly to address emerging challenges and shifting organizational priorities at short notice.
- Data
Fluency: Tracks record of driving complex, data-focused initiatives with a deep understanding of data governance, quality challenges, and architecture in large organizations.
- Conflict Resolution & Alignment: Reconciles competing stakeholder priorities and disparate business requirements into unified, deliverable roadmaps via targeted engagement, workshops, and governance forums.
- Role - Hybrid Senior Data Analyst – London – 3 days a week in the office
- Location - London
- Type – Permanent
StudySmarter Expert Advice🤫
We think this is how you could land SC - Data Analyst
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Velocity Talent!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like SC - Data Analyst at Velocity Talent.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Velocity Talent.
✨Apply Directly through Our Website
When you find a suitable opening like SC - Data Analyst at Velocity Talent, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace SC - Data Analyst
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Velocity Talent, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Velocity Talent. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Velocity Talent
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Velocity Talent!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
