At a Glance
- Tasks: Design and maintain data models for analytics and regulatory compliance in the insurance sector.
- Company: Leading insurance firm focused on innovation and data excellence.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Join a dynamic team driving data standardisation and governance.
- Why this job: Shape the future of insurance data with cutting-edge modelling techniques.
- Qualifications: Experience in data modelling, insurance standards, and tools like Erwin Data Modeler.
The predicted salary is between 60000 - 75000 £ per year.
We are seeking an experienced Data Modeler / Architect with strong insurance industry standards knowledge and a solid foundation in modern data modelling practices.
- The ideal candidate will have hands-on experience with modelling tools, data frameworks, and insurance industry data exchange standards.
- This role involves designing scalable, compliant, and high-quality data structures that support enterprise analytics, regulatory reporting, and operational data needs.
- Design and maintain enterprise-wide data models (conceptual, logical, physical) to support analytics, operational reporting, regulatory compliance, and integration use cases.
- Own the design of canonical data models for delegated insurance covering Contract, Premium/Risk, and Claims, including full transaction and movement-based constructs (e.g. endorsements, cancellations, reinstatements, claim financial movements).
- Translate conceptual and logical models into implementation-ready artefacts including JSON/XML schemas and Excel bordereaux templates to support real-time API ingestion from MGA/TPA partner systems and monthly bordereaux submissions.
- Develop data models using Dimensional (Star/Snowflake), Data Vault, and 3NF methodologies.
- Participate in governance forums to drive standardization across data domains.
- Define and govern integration patterns for third-party datasets including geocoding, hazard, valuation, and reference data.
- Interpret and apply ACORD and CSIO data standards for global and Canadian insurance data exchange.
- Align modelling standards with the GSI Data Target Operating Model (TOM) and Partner Management & Data Intake workstreams acting as the architectural authority for delegated data standards.
- Lead data modelling workshops and SME councils to drive stakeholder alignment.
- Knowledge of ACORD (global, comprehensive insurance data standards).
- Knowledge of CSIO (Canadian insurance standards, including XML, EDI, and JSON formats).
- Erwin Data Modeler – Mandatory.
- Medallion Data Architecture.
- MAR/SOX data governance and regulatory frameworks.
- Data Vault Modelling.
- JSON/XML schemas.
- Experience with MDM / RDM (Master Data Management / Reference Data Management).
Data Modeler/ Architect- P&C Insurance in City of London employer: ValueMomentum
Join a forward-thinking company that values innovation and excellence in the insurance sector, where your expertise as a Data Modeler/Architect will directly contribute to shaping robust data structures that drive enterprise analytics and compliance. Our collaborative work culture fosters continuous learning and professional growth, offering you the opportunity to lead impactful projects while working alongside industry experts in a dynamic environment. Located in a vibrant area, we provide a supportive atmosphere that encourages creativity and teamwork, making us an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Modeler/ Architect- P&C Insurance in City of London
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We think you need these skills to ace Data Modeler/ Architect- P&C Insurance in City of London
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 ValueMomentum, 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 ValueMomentum. 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 ValueMomentum
✨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 ValueMomentum!
✨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.
