About the Role:

Grade Level (for internal use):

About the Role:

The Team: The data science team is responsible for extracting insights and knowledge from complex datasets to create new products and solve strategic business problems. What sets this team apart is its emphasis on empirical evidence and continuous learning, valuing a balance between technical rigor, creativity in problem-solving, and a strong commitment to producing tangible value through data-driven solutions. Currently, the team is focusing on the implementation of a few GenAI-powered enterprise-scale projects.

The Responsibilities & Impact:  A lead data scientist significantly contributes to the business by leading advanced GenAI-powered projects and mentoring junior team members. This work positively impacts clients by delivering more accurate predictions, personalized experiences, and innovative solutions that ultimately foster greater customer satisfaction and competitive advantage.

• Lead data scientists in developing and implementing cutting-edge large-scale generative AI and LLM-powered systems.
• Collaborate with cross-functional teams, including engineers, credit risk business experts, and product managers to understand business requirements, and design and develop LLM-based solutions.
• Apply statistical analysis and ML techniques to extract meaningful insights from large-scale financial datasets.
• Research and evaluate new methodologies, tools, and algorithms in the field of data-driven credit risk analytics and AI to improve products’ accuracy and efficiency.
• Efficiently communicate results to both technical and non-technical stakeholders through presentations, visualizations, and reports.
• Stay updated with the latest advancements in Generative AI to contribute to product innovation effectively.

Compensation/Benefits Information: 

S&P Global states that the anticipated base salary range for this position is $88,700 – $195,800.

 The final base salary for this role will be based on the individual’s geographical location as well as experience and qualifications for the role.  

In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan. 

This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, visit Our Benefits (spgbenefits.com) . 
Take the reins on cutting-edge data initiatives, influencing strategic direction and driving innovation through advanced analytics and modeling.

What We’re Looking For:

Basic Qualifications

• Play a pivotal role in shaping the team's growth by mentoring junior members and fostering a culture of continuous learning, both personal and professional development.
• Collaborate with cross-functional teams to transform data insights into actionable business strategies, positively impacting clients and markets through data-driven solutions. Assume a key role in thought leadership, utilizing your expertise to guide the organization's data strategy and establish a reputation as an industry expert in data science and analytics.
• A master’s or Ph. D. degree in Computer Science, Physics or Applied Mathematics or a related field with a focus on Deep Learning and NLP.
• Experience in leading data science projects with a strong background in financial risk and deep learning.
• Proficiency in programming languages such as Python and experience with deep learning frameworks and cloud-based computational platforms.
• In-depth understanding of statistical analysis combined with critical thinking and problem-solving skills.
• Ability to mentor and guide junior data scientists.
• Curiosity and willingness to lean new technologies and advancements in Deep Learning, GenAI, and beyond.
• Ability to collaborate across the board to contribute to the development of the overall data science strategy and vision.

Right to Work Requirements:

This role is limited to persons with indefinite right to work in the United States.

Return to Work 

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