At a Glance
- Tasks: Lead customer data operations and mentor junior team members in a dynamic environment.
- Company: Join CUBE, a forward-thinking company focused on data excellence and innovation.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative team atmosphere with a focus on continuous improvement and innovation.
- Why this job: Make a real impact by shaping customer data practices and driving automation.
- Qualifications: Experience in risk and controls within financial services, strong data analysis skills.
The predicted salary is between 60000 - 80000 £ per year.
This role provides senior expertise in Operational Risk and Risk Controls, applying it through customer data processing and analysis, ensuring data quality, governance, and strategic utilisation. It develops data standards, advises on complex data challenges, utilises and implements AI solutions and supports major customer initiatives within CUBE. The role mentors junior team members and shapes customer data practices.
Key Responsibilities
- Actively contribute to CUBE’s success by supporting the delivery of the Data & Analytics team’s goals.
- Play a leading role in the execution of all aspects of Customer Data Operations on a prioritised basis.
- Matching of risks and controls.
- Index build.
- Index management.
- Other data expansion.
- Contribute to the consistent application of CUBE’s Data Technical Standards to core risk and control content and beyond.
- Contribute to the ongoing development of CUBE’s business rules which form the basis for CUBE’s index assets.
- As someone with subject matter expertise, contribute to data processing exercises on a prioritised basis as required (particularly matching and index building).
- Actively seek opportunities to engage with the rest of D&A (and wider CUBE as appropriate) to improve data and processes.
- Collaborate closely with other members of the D&A team to support cross-team working and understanding.
- Actively support the CUBE-wide objective to automate.
- Collaborating with CUBE’s Product, Engineering, and Data Science teams to facilitate faster and better data processing.
- Leadership and mentorship of more junior members of the team, supporting their development in line with business needs.
Skills & Competencies
- Data Management & Quality: Oversees enterprise-wide data architecture and governance practices. Ensure consistency, reliability, and traceability in data assets.
- Risk & Governance: Acts as subject matter expert on governance, risk, and compliance. Embeds control standards across operational processes.
- Tools, Automation & AI: Leads automation and integration initiatives, embedding AI/ML where relevant. Establishes tool standards and governance.
- Problem-Solving & Innovation: Champions innovation in automation and process optimization. Promotes continuous improvement and data-driven decision-making.
- Communication & Collaboration: Leads cross-functional discussions, influencing key stakeholders through data-driven recommendations.
- Operational Execution: Aligns data operations execution with strategic business goals, driving governance and consistency.
- Mentoring & Leadership: Mentors team members across teams, developing strong technical and professional capability.
Required Experience & Qualifications
- Able to demonstrate a strong knowledge of risks and controls having gained extensive experience in a financial services risk and control front line role (e.g. Business Risk & Control Officer, Supervisor).
- Highly knowledgeable on the key risks faced by our clients, e.g. market manipulation, unauthorised trading, resilience.
- Deep understanding of NFRM core processes, e.g. RCSA, incident management, read across / lessons learned.
- Experienced with internal audit, external audit and ideally regulators – and understanding of areas of regulatory scrutiny targeting governance and controls (e.g. SMCR).
- Able to clearly and succinctly articulate and promote CUBE’s risk and control product offering.
- Ability to work in a fast-paced Regtech environment producing work to a high standard under time pressure.
- A pragmatic self-starter with the ability to work independently and as part of a team.
- Strong organisational skills, with impeccable attention to detail and proven ability to manage multiple projects with varying and time-pressured deliverables.
- Flexible, supportive, collaborative, contributing positively to our strong team dynamic and culture.
- Ability to clearly communicate technical concepts to non-technical stakeholders.
- Concise written and verbal communication skills.
- Extensive MS Office skills, particularly Excel.
- Proficiency in at least one of the following data analysis tools and languages, such as Python, SQL, MS/Azure Foundry and data visualisation tools (e.g., Tableau, Power BI).
- Experience mentoring to achieve excellence.
CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Customer Data SME employer: Cube Asia
CUBE is an exceptional employer that fosters a collaborative and innovative work culture, where employees are empowered to lead and mentor while contributing to cutting-edge data solutions in the financial services sector. With a strong commitment to employee growth, CUBE offers extensive training opportunities and encourages continuous improvement, ensuring that team members thrive in a dynamic Regtech environment. Located in a vibrant area, CUBE provides a supportive atmosphere that values diversity and inclusion, making it an ideal place for professionals seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Customer Data SME
✨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 Cube Asia!
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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 Cube Asia.
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We think you need these skills to ace Customer Data SME
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 Cube Asia, 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 Cube Asia. 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 Cube Asia
✨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 Cube Asia!
✨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.
