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For Companies At a Glance
- Tasks: Analyse large datasets and communicate findings to senior analysts.
- Company: Join S&P Global Ratings, a leader in credit ratings and financial insights.
- Benefits: Work on high-profile projects with exposure to global credit markets.
- Why this job: Shape data-driven research initiatives and engage with diverse stakeholders.
- Qualifications: 3-5 years in data science; degree in a quantitative field required.
- Other info: Opportunity for remote work and collaboration across teams.
The predicted salary is between 36000 - 60000 £ per year.
About the Role:
Grade Level (for internal use): 11
The Role: Data Scientist, Credit Research & Insights
The Team: The Credit Research & Insights team, within S&P Global Ratings Research, provides timely credit research and insight in relation to global credit and rating performance trends. The team generates leading-edge high frequency credit research which is widely used throughout the firm and by external stakeholders.
The Impact: S&P Global Ratings Credit Research & Insights team is looking for an experienced data scientist who will play a crucial role in shaping and managing the team’s data-driven research projects. This role serves as the backbone to all the team’s data science related projects. The ideal candidate should be highly motivated, goal-oriented and be able to work independently on data science projects. She or he will need to interact with senior analysts and management across the firm as well as senior external parties.
What’s in it for you:
- Opportunity to work on high profile credit research projects and reports, which are extensively read outside the firm.
- Ability to influence and shape future data driven global research initiatives, using extensive proprietary datasets.
- Highly visible role with exposure to and engagement with multiple teams and stakeholders across the organization.
- Opportunity to work with an extensive list of proprietary datasets, as well as external sources, and be the original source of new research initiatives.
- Exposure to global credit markets including multiple asset classes (corporates, public finance, structured finance, sovereigns).
- Engagement with external stakeholders.
Responsibilities:
- Organize and analyze large data sets and be able to communicate your findings to senior analysts.
- Undertake pre-processing of structured and unstructured data.
- Drive both business decisions and research based on the insights obtained from the data.
- Be able to use natural language processing to analyze internal and external data.
- Propose data solutions and strategies to business challenges and opportunities.
- Assist with improving data efficiencies and processes across the team.
- Conduct quantitative and qualitative credit research, and various statistical analysis to analyze trends.
- Monitor and analyze key global market credit trends.
- Manage Access and Oracle databases, including writing queries.
- Write commentary to support research observations.
- Meet rigorous publishing deadlines.
- Interpret and articulate research report findings for external clients, and internal stakeholders.
- Stay actively abreast of financial market events and their implications.
What We are Looking For:
Basic Qualifications:
- 3-5 years of experience in a data science role.
- Degree in a highly quantitative field: Computer Science, Machine Learning, Statistics, Mathematics, etc.
- Proficiency with data mining, knowledge of probability theory and advanced statistical techniques.
- Experience with regression analysis (beyond linear regression), supervised learning, unsupervised learning or time-series analysis.
- Experience with scientific scripting languages (Python, R, Matlab).
- Experience accessing and manipulating data in SQL database environments.
- Experience presenting to internal and external audiences.
- Comfortable working in a dynamic, fast-paced environment.
- Team player with track record of collaboration with cross functional and cross regional teams.
- Demonstrated ability to self-manage, take initiative, and meet deadlines.
Preferred Qualifications:
- Advanced degree in quantitative field preferred.
- Prior experience working in a research capacity within financial markets.
About S&P Global Ratings
At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clarity so market participants can uncover opportunities and make decisions with conviction.
S&P Global Ratings is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets.
For more information, visit www.spglobal.com/ratings
Equal Opportunity Employer
S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law.
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Contact Detail:
WeAreTechWomen Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist, Credit Research & Insights
✨Tip Number 1
Familiarise yourself with the latest trends in credit research and data science. Being well-versed in current methodologies and tools will help you engage in meaningful conversations during interviews and demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the credit research and data science sectors. Attend industry events or webinars, and connect with current employees at S&P Global on platforms like LinkedIn to gain insights into the company culture and expectations.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully applied data science techniques, especially in financial contexts. Highlight your experience with SQL databases and any relevant statistical analysis to showcase your technical skills.
✨Tip Number 4
Stay updated on global credit market events and their implications. This knowledge will not only help you in interviews but also show your commitment to understanding the broader context of the role you're applying for.
We think you need these skills to ace Data Scientist, Credit Research & Insights
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in credit research and insights. Emphasise your proficiency with data mining, statistical techniques, and any experience with financial markets.
Craft a Strong Cover Letter: In your cover letter, explain why you are passionate about the role and how your skills align with the responsibilities outlined in the job description. Mention specific projects or experiences that demonstrate your ability to manage data-driven research.
Showcase Technical Skills: Clearly list your technical skills, especially in programming languages like Python or R, and your experience with SQL databases. Provide examples of how you've used these skills in previous roles to drive business decisions or research.
Prepare for Interviews: If selected for an interview, be ready to discuss your past projects in detail. Prepare to explain your approach to data analysis, how you handle large datasets, and your experience presenting findings to both technical and non-technical audiences.
How to prepare for a job interview at WeAreTechWomen
✨Showcase Your Data Skills
Be prepared to discuss your experience with data mining, statistical techniques, and programming languages like Python or R. Highlight specific projects where you've successfully applied these skills, especially in a financial context.
✨Understand the Credit Market
Familiarise yourself with current trends in global credit markets. Being able to discuss recent developments and their implications will demonstrate your engagement and understanding of the industry.
✨Prepare for Technical Questions
Expect technical questions related to regression analysis, supervised and unsupervised learning, and SQL database manipulation. Brush up on these topics and be ready to solve problems on the spot.
✨Communicate Clearly
Since the role involves presenting findings to senior analysts and external stakeholders, practice articulating complex data insights in a clear and concise manner. Use examples from your past experiences to illustrate your points.