Data Scientist at S&P Global

Mexico City, Mexico City, Mexico

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Financial Services, Market IntelligenceIndustries

Requirements

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
Nice to have: Cloud expertise (AWS and GCP preferably)
Nice to have: Expertise in deploying machine learning models in cloud environments
Nice to have: Familiarity in working with LLMs

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

Skills

Key technologies and capabilities for this role

Machine LearningNatural Language UnderstandingData ExtractionInformation RetrievalExploratory Data AnalysisProof-of-Concept ModellingModel BenchmarkingModel ValidationLarge Model TrainingProduction PipelinesCode ReviewModel DeploymentModel Scaling

Questions & Answers

Common questions about this position

What experience level is required for this Data Scientist role?

The role requires 2+ years of professional experience in the Data Science domain.

What technical skills are essential for this position?

Expertise in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace), SOTA NLP models including sentence transformers and word embeddings, probabilistic machine learning for classification/regression/clustering, feature engineering, SQL, and Linux OS is required.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What is the team environment like at S&P Global for this role?

You will work in a truly global team in a highly engaging work environment, collaborating with a highly skilled and technically strong team, encouraged for thoughtful risk-taking and self-initiative.

What makes a strong candidate for this Data Scientist position?

Candidates with 2+ years in Data Science, expertise in Python and NLP/SOTA models, experience in production ML pipelines, feature engineering for large datasets, plus skills in SQL, Linux, Git, OOP design patterns, and strong problem-solving stand out.

S&P Global

Provides financial information and analytics services

About S&P Global

S&P Global provides financial information and analytics to a wide range of clients, including investors, corporations, and governments. The company offers services such as credit ratings, market intelligence, and indices, which help clients understand and navigate the global financial market. S&P Global's products work by utilizing advanced data analytics and research to deliver insights that assist clients in making informed decisions and managing risks. Unlike many competitors, S&P Global has a diverse range of divisions, including S&P Global Ratings and S&P Dow Jones Indices, which allows it to cater to various financial needs. The company's goal is to support clients in driving growth while also committing to corporate responsibility and positive societal impact.

New York City, New YorkHeadquarters

1917Year Founded

IPOCompany Stage

Data & Analytics, Financial ServicesIndustries

10,001+Employees

Benefits

Health Insurance

Unlimited Paid Time Off

Professional Development Budget

401(k) Company Match

Family Planning Benefits

Employee Discounts

Risks

Integration challenges with new acquisitions like ProntoNLP may cause operational issues.

Increased competition from AI-driven platforms like Brooklyn Investment Group.

Dependence on volatile credit ratings market could impact revenue stability.

Differentiation

S&P Global integrates advanced AI tools for superior financial analytics capabilities.

The company offers comprehensive ESG solutions, meeting growing sustainability demands.

S&P Global's diverse divisions provide a wide range of financial services globally.

Upsides

Acquisition of ProntoNLP boosts data analytics and sentiment scoring capabilities.

Rising demand for ESG data enhances S&P Global's market position.

Expansion into India strengthens S&P Global's research and insights offerings.

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