Key responsibilities and skills:
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p global seeks a lead data scientist to join its enterprise data organization. As a key member of the collection platforms & ai – cognitive engineering team, you will play a vital role in building genai-driven and ml-powered products and capabilities.
this includes defining ai strategy, mentoring junior data scientists, driving production-ready ai products and pipelines, and working in a truly global team.
we are looking for an individual who is passionate about solving high-complexity, high-impact problems end-to-end, architecting and overseeing production-ready pipelines from ideation to deployment.
responsibilities include:
- defining ai roadmap, tooling choices, and best practices for model building, prompt engineering, fine-tuning, and vector retrieval systems
- architecting, developing, and deploying large-scale ml and genai-powered products and pipelines
- owning all stages of the data science project lifecycle, including identification and scoping of high-value data science and ai opportunities
- partnering with business leaders, domain experts, and end-users to gather requirements and align on success metrics
- evaluating, interpreting, and communicating results to executive stakeholders
- leading exploratory data analysis, proof-of-concepts, model benchmarking, and validation experiments for both ml and genai approaches
- establishing and enforcing coding standards, performing code reviews, and optimizing data science workflows
- driving deployment, monitoring, and scaling strategies for models in production (including both ml and genai services)
- mentoring and guiding junior data scientists; fostering a culture of continuous learning and innovation
- managing stakeholders across functions to ensure alignment and timely delivery
requirements:
- hands-on experience with large language models (e.g., openai, anthropic, llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
- expert proficiency in python (numpy, pandas, spacy, scikit-learn, pytorch/tf 2, hugging face transformers)
- deep understanding of ml & deep learning models, including architectures for nlp (e.g., transformers), gnns, and multimodal systems
- strong grasp of statistics, probability, and the mathematics underpinning modern ai
- ability to surf and synthesize current ai/ml research, with a track record of applying new methods in production
- proven experience on at least one end-to-end genai or advanced nlp project: custom ner, table extraction via llms, q&a systems, summarization pipelines, ocr integrations, or gnn solutions
- familiarity with orchestration and deployment tools: airflow, redis, flask/django/fastapi, sql, r-shiny/dash/streamlit
- openness to evaluate and adopt emerging technologies and programming languages as needed
- master's or ph.d. in computer science, statistics, mathematics, or related field (minimum bachelor's)
- 6+ years of relevant experience in data science/ai, with at least 2 years in a leadership or technical lead role
- prior experience in the economics/financial industry, especially with market-intelligence or risk analytics products
- public contributions or demos on github, kaggle, stackoverflow, technical blogs, or publications
work location: mexico city, santa fe (2 days a week onsite)