Overview As a member of the Data Transformation team you will work on building ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P; Global Market Intelligence and our clients. You will spearhead development of production-ready AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) integral team and encouraged for thoughtful risk-taking and self-initiative.
What’s in it for you Be a part of a global company and build solutions at enterprise scale
Collaborate with a highly skilled and technically strong team
Contribute to solving high complexity, high impact problems
Key Responsibilities Design, Develop and Deploy ML powered products and pipelines
Play a central role in all stages of the data science project life cycle, including: Identification of suitable data science project opportunities
Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements
Evaluation/interpretation of results and presentation to business leaders
Performing exploratory data analysis, proof-of-concept modelling, model benchmarking and setup model validation experiments
Training large models both for experimentation and production
Develop production ready pipelines for enterprise scale projects
Perform code reviews & optimization for your projects and team
Spearhead deployment and model scaling strategies
Stakeholder management and representing the team in front of our leadership
Leading and mentoring by example including project scrums

What We’re Looking For 2+ years of professional experience in Data Science domain
Expertise in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.)




Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures
Expertise in probabilistic machine learning model for classification, regression & clustering
Strong experience in feature engineering, data preprocessing, and building machine learning models for large datasets
Exposure to Information Retrieval, Web scraping and Data Extraction at scale
OOP Design patterns, Test-Driven Development and Enterprise System design
SQL (any variant, bonus if this is a big data variant)
Linux OS (e.g. bash toolset and other utilities)
Version control system experience with Git, GitHub, or Azure DevOps
Problem-solving and debugging skills
Software craftsmanship, adherence to Agile principles and taking pride in writing good code
Techniques to communicate change to non-technical people
Nice to have Prior work to show on Github, Kaggle, StackOverflow etc.
Cloud expertise (AWS and GCP preferably)
Expertise in deploying machine learning models in cloud environments
Familiarity in working with LLMs
Location Mexico City (Santa Fe, 2-3 days onsite a week)
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. Only electronic job submissions will be considered for employment.
If you need an accommodation during the application process due to a disability, please send an email to: [email protected] and your request will be forwarded to the appropriate person.
Seniority level Mid-Senior level
Employment type Full-time
Job function Information Technology
Industries: Financial Services, Information Services, and Data Infrastructure and Analytics

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