Data Scientist

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Collaborate with Product and Engineering teams to pinpoint high-impact opportunities, clarify ambiguous challenges, establish success metrics, and select practical methodologies (heuristics, statistics, ML, or GenAI).

• Spearhead thorough experimentation across teams, including hypothesis formulation, metric and guardrail identification, power analysis, A/B testing (or quasi-experiments), and concise readouts that inform decision-making.

• Develop and refine ML/AI capabilities that are deployed to production (e.g., classification, information extraction, ranking/recommendations, and GenAI components like RAG or creating agent harnesses for core agentic journeys), focusing on value addition, latency, and cost efficiency.

• Implement best-in-class evaluation methods for both ML and LLM features: creation of golden datasets, offline and online evaluation strategies, regression test suites, and monitoring systems that detect quality degradation early.

• Empower engineers to safely and effectively utilize AI by providing guidance on prompt patterns, tool/function calling, structured outputs, guardrails, and debugging/evaluation processes.

• Design and facilitate agentic workflows that deliver genuine product value, ensuring clear constraints, observability, and fallback options.

• Oversee the complete lifecycle of deployed models and AI systems, addressing data requirements, training/fine-tuning as necessary, validation, deployment, monitoring, incident response, and ongoing enhancements.

• Enhance organizational leverage by creating reusable assets (evaluation harnesses, shared datasets, templates, documentation) and conducting enablement workshops.

• Clearly communicate insights and trade-offs to both technical and non-technical stakeholders, translating analyses into actionable decisions and measurable impacts.

• Advocate for responsible, privacy-conscious AI practices: ensuring appropriate data handling, addressing bias/fairness considerations where relevant, and establishing human-in-the-loop workflows when necessary.

⛳️ Requirements

• 3+ years (or equivalent) of experience delivering data science projects that have been deployed to production and/or significantly influenced product direction.

• Proven experience in cross-functional collaboration and effective communication with a diverse range of stakeholders; ability to influence without direct authority.

• Proficient in Python and SQL, with the capability to write maintainable, production-quality code (including testing, reviews, and documentation).

• Demonstrated ability to mentor and enable others—assisting engineers and teams in adopting best practices and delivering higher quality work more swiftly.

• At least 3 of the following:

• Strong applied statistics and experimentation expertise (A/B testing, causal reasoning, metric design, interpretation under uncertainty).

• Proven capability to assess and enhance models in real-world conditions: dataset design, error analysis, offline metrics, online measurement, monitoring, and iteration.

• Practical experience building with LLMs in product settings, including aspects like RAG/grounding, tool/function calling, structured outputs, prompt iteration, and managing quality/cost/latency trade-offs.

• Hands-on approach to LLM evaluation: golden sets, regression testing, human review loops, and monitoring for quality drift.

• Familiarity with modern MLOps/LLMOps methodologies (experiment tracking, ETL pipelines, versioning, CI/CD for ML, observability).

• Experience with NLP and information extraction/classification on unstructured social/content data.

• Background in developing and evaluating large-scale Retrieval, Recommendation, and Search Systems.

🏝️ Benefits

• Competitive Salary

• Remote Work Options with Hybrid Flexibility and Home Office Set-Up Stipend

• Coworking Office Subscription for Collaborative Spaces

• Health, Dental, and Life Insurance Coverage*

• Open Vacation Policy and Flexible Holiday Schedule to Suit Your Needs

• Paid Parental Leave to Support Quality Time with Your Loved Ones

• Career Development, including Internal and External Training Opportunities