At a Glance
- Tasks: Deliver high-quality data solutions and support in a fast-paced, client-facing environment.
- Company: Join Moody's, a global 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 focused on operational excellence and innovative data solutions.
- Why this job: Make a real impact by transforming data into actionable insights with cutting-edge technology.
- Qualifications: Strong skills in SQL and Python, with a passion for data quality and AI.
The predicted salary is between 70100 - 98000 £ 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 do this by striving 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- Strong technical expertise in SQL and Python for data analysis, validation, and remediation, enabling accurate and scalable data operations.
- Proven experience in data quality management and remediation processes, ensuring completeness, consistency, and reliability of large datasets.
- Ability to operate in fast-paced, client-facing environments, managing competing priorities and delivering against tight deadlines and service level agreements.
- Experience coordinating cross-functional stakeholders and contractor resources to maintain operational continuity and quality output.
- Knowledge of data processing frameworks, including ETL pipelines, data integration, and data modeling (experience with Databricks or Spark preferred).
- Strong analytical and problem-solving skills with the ability to communicate clearly to both technical and 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.
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
- Deliver high-quality data remediation and operations support, ensuring accurate, timely, and scalable data solutions in a client-facing environment.
- Act as a primary point of contact for data remediation issues, triaging, prioritizing, and resolving critical client-facing data incidents.
- Execute remediation activities using SQL and Python to analyze, validate, and improve data quality across multiple datasets.
- Monitor and enhance data quality by ensuring accuracy, completeness, and consistency through structured processes and controls.
- Execute data workflows, pipelines, and integration processes to support efficient and reliable data operations.
- Identify and implement opportunities for automation and process improvements to enhance operational efficiency.
- Coordinate contractor resources, including task allocation, onboarding support, and quality oversight to ensure consistent delivery.
- Track remediation activities, maintain documentation, and monitor progress against timelines, service levels, and operational targets.
- Produce operational reporting on volumes, trends, risks, and performance metrics to support decision-making.
- Collaborate with cross-functional teams to address root causes, improve remediation playbooks, and align with data strategy objectives.
- Escalate complex or high-risk issues with structured insights and recommendations to support timely resolution.
Our Data Estate team is responsible for delivering high-quality, trusted commercial data products to clients globally. The team contributes to Moody’s by providing comprehensive and reliable data solutions that support critical business decisions, while driving data quality and operational excellence through scalable remediation and governance practices. It also enhances the accessibility and usability of data through efficient processing, integration, and analytics capabilities. By joining the team, you will be part of a fast-paced, client-focused environment, working on one of the world’s leading company data platforms.
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.
Assistant Director - Data Specialist employer: Moody's
Moody's is an exceptional employer that champions inclusivity and innovation, making it a fantastic place for professionals in the data field. With a strong commitment to employee growth, you will have access to cutting-edge technology and the opportunity to work alongside diverse teams in a dynamic environment. The company fosters a culture of collaboration and curiosity, ensuring that every voice is heard and valued, while also providing meaningful career development opportunities in the heart of a global leader in risk assessment.
StudySmarter Expert Advice🤫
We think this is how you could land Assistant Director - Data Specialist
✨Get Involved in Data Science Meetups
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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 Moody's.
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We think you need these skills to ace Assistant Director - 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!
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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.