At a Glance
- Tasks: Support and enhance data quality, manage datasets, and collaborate with global teams.
- Company: Join Moody's, a leader in risk assessment and an inclusive employer.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Be part of a dynamic team driving innovation in data solutions.
- Why this job: Make a real impact by transforming data into actionable insights.
- Qualifications: 1-3 years in data operations, strong SQL and Python skills required.
The predicted salary is between 45000 - 55000 £ per year.
This job is with Moody's, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We strive to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Skills and Competencies
- 1–3 years’ experience in data operations, data management, analytics, or automation, enabling effective handling and transformation of large datasets
- Strong SQL proficiency (e.g., PostgreSQL, MySQL, SQL Server) to extract, transform, and optimize data for reporting and operational use
- Hands-on Python experience (Pandas, NumPy) for data manipulation and analysis, supporting scalable data workflows
- Understanding of data architecture, data modeling, and ETL processes to ensure efficient data integration and pipeline development
- Experience implementing data quality frameworks to ensure accuracy, consistency, and completeness of datasets
- Strong communication and problem-solving skills to collaborate across global teams and translate complex data insights into actionable outputs
- Familiarity with data platforms such as Databricks, Spark, Snowflake, or similar technologies
- Ability to communicate technical concepts clearly to non‑technical stakeholders
- Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency
- Interest in exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use
Education
- Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field
Responsibilities
- Support and enhance data quality and operations across multiple sources, ensuring reliable, scalable, and efficient data delivery.
- Develop and execute processes to monitor, manage, and improve data quality across datasets
- Design and implement data deduplication frameworks to improve data accuracy and usability
- Analyze and optimize data operations workflows, identifying automation opportunities to increase efficiency
- Collaborate with cross-functional teams (Sales, Product, Technology) to align data solutions with business needs
- Support stakeholders by delivering data insights and responding to data-related queries
- Contribute to the development and enhancement of enterprise data platforms, ensuring integrity and scalability
- Maintain best practices in data governance, data modeling, and pipeline optimization
About the Team
Our Data Estate team is responsible for delivering high-quality, mission-critical data that powers decision-making across global markets. We provide comprehensive company data through flagship platforms such as Orbis, we enable clients to access, analyze, and act on complex datasets efficiently, and we drive continuous improvements in data quality, accessibility, and operational excellence. By joining our team, you will contribute to innovative data solutions supporting global customers across industries.
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
Senior Data Specialist employer: Moody's
At Moody's, we pride ourselves on being an inclusive employer that champions diversity and innovation. Our collaborative work culture fosters personal and professional growth, providing employees with opportunities to engage in meaningful projects that shape the future of risk assessment. Located in a vibrant environment, we offer competitive benefits and a commitment to employee well-being, making Moody's an exceptional place to advance your career as a Senior Data Specialist.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Specialist
✨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 Moody's!
✨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 Senior Data Specialist at Moody's.
✨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 Moody's.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Specialist at Moody's, 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 Senior Data Specialist
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 Moody's, 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 Moody's. 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 Moody's
✨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 Moody's!
✨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.
