Top Data Science Jobs in Mexico

Leads AI-enabled risk modeling services, setting strategy, managing client relationships, overseeing machine learning and predictive analytics solutions, and guiding end-to-end delivery. The role includes model governance, feature engineering, performance evaluation, innovation, cross-functional collaboration, team coaching, thought leadership, and business development across risk modeling engagements.

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

Configure and implement Fenergo solutions for AML and sanctions compliance, translating business and regulatory requirements into effective system configurations. Analyze complex data, apply advanced analytics and AI fluency, develop client business cases, demonstrate FenX capabilities, improve processes, engage stakeholders, and manage team members while delivering strategic consulting insights.

Physician-led clinical AI role translating healthcare workflow challenges into AI models and product features. Responsibilities include validating models with Latin American clinical data, conducting hospital and clinic pilots, adapting protocols to Mexican regulations, gathering physician feedback, supporting onboarding, and communicating clinical insights to product, engineering, and commercial teams.

Lead vision, strategy, and execution for AI-powered features in Coupa's Supplier Network. Drive two-sided marketplace growth, monetization, trust/identity, and product-led growth by partnering with engineering, AI/ML, data science, and commercial teams. Define success metrics, engage customers, and monitor AI and marketplace trends to increase liquidity, revenue, and platform differentiation.

Analyze and improve data ingestion processes, data quality, reporting standards, and operational performance. Validate loading statistics, cleanse data, resolve inconsistencies, execute testing, track project milestones, document procedures, and coordinate data requirement changes with business, technology, supplier, and client stakeholders. Develop metrics and reports, support reporting entities, and implement data solutions that improve efficiency, reliability, and service quality.

Leads senior client relationships and multi-market media planning for priority accounts across LATAM. Provides strategic, data-driven guidance on media investment, performance, optimization, KPIs, governance, and business growth. Oversees complex planning workstreams, collaborates with activation and analytics teams, and develops planning capabilities, standards, talent, and quality frameworks. Acts as a trusted senior advisor while driving alignment across global, regional, and cross-functional stakeholders.

Lead four product managers and own PayJoy’s end-to-end onboarding strategy across digital and in-store channels. Drive application, direct-to-consumer, enterprise, and offers/risk product areas; optimize conversion and acquisition costs; guide global versus localized solutions for new markets; ensure regulatory compliance; and collaborate with Engineering, Design, Data, Risk, and Operations to deliver scalable consumer fintech experiences.

Owns end-to-end technical program delivery for launching and scaling financial products across LATAM and South Africa. Coordinates Product, Engineering, Legal, Risk, Design, Operations, vendors, and country teams; manages roadmaps, dependencies, testing, launch readiness, compliance documentation, production operations, and post-launch optimization. Builds repeatable launch playbooks, drives UAT and pilot rollouts, tracks risks and defects, and provides structured status updates to leadership.

Develop and maintain clinical trial eSource databases using ClinSpark, collaborate with site staff on database requirements, ensure protocol and regulatory compliance, document database builds, and improve programming processes. The role requires clinical data science and programming experience, attention to detail, strong communication, English proficiency, and familiarity with clinical trial lifecycle processes.

The Staff Engineer, Data Science role focuses on leveraging tech skills to enhance team capabilities and provide advanced solutions for client challenges.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Design and implement Industry 4.0 solutions (IoT, AI/ML, robotics, AR/VR, 3D printing, Big Data) to optimize operational and office processes. Integrate with ERP (SAP), MES, PLCs, robots and databases, ensure SOX compliance, support cloud and on-prem deployments, and develop BI/analytics solutions.

Develop machine learning models and production analytics using large healthcare datasets for disease detection, patient outcome prediction, patient identification, and HCP targeting. Translate client requirements into scalable deliverables, validate new methodologies through client work, collaborate with engineering and product teams to productionize solutions, contribute to AI/ML proofs of concept, and mentor junior team members.

Lead paid media analytics for Life Company, using SQL/Python and advanced statistics to measure and optimize paid social/search and AI-powered search. Build audience segmentation, run incrementality/experimentation, create visualizations and recommendations, and partner with marketing to drive acquisition and engagement.

Leads clinical data science review and delivery activities across study lifecycles for Mexico and Colombia. Responsibilities include planning milestones, reviewing clinical data for meaningful errors, managing timelines, budgets, resources, risks, and deliverables, coordinating cross-functional teams and clients, supporting clinical system development, participating in audits, and escalating issues. Requires clinical data management experience, clinical data systems proficiency, analytics and validation expertise, project leadership, and approximately 15% travel.

As a Senior Clinical Data Science Lead, you will oversee clinical data activities, ensure data quality, manage budgets, and participate in audits. You will lead data review efforts and communicate effectively with stakeholders, ensuring deliverables meet timelines and quality standards.

Leads data science strategy across Mexico and Brazil, manages and mentors a distributed team, and remains hands-on building and deploying machine learning models. Establishes modeling standards, infrastructure, delivery practices, and technical roadmaps while partnering with credit leadership on underwriting, valuation, impact measurement, and P&L analysis. Requires strong applied machine learning expertise, prior data science leadership, business communication skills, and understanding of credit or underwriting.

Leads AI and data science strategy across machine learning, NLP, search, recommendation, experimentation, and generative AI. Manages technical teams, develops AI talent, oversees systems from experimentation through production, establishes evaluation and responsible AI frameworks, and partners with product, technology, and business leaders to shape roadmaps and deliver measurable customer and business outcomes.

Leads AI and data science strategy across machine learning, NLP, search, recommendation, experimentation, and generative AI. Manages technical teams, develops talent, and oversees AI systems from experimentation through production. Builds LLM, RAG, semantic search, and knowledge-discovery solutions; establishes evaluation frameworks, quality metrics, experimentation practices, and responsible AI standards. Partners with product, technology, and business leaders to shape roadmaps and deliver measurable customer and business outcomes.

Supports data science projects by exploring large datasets, creating templates and summaries, automating processes, developing analytical solutions, and collaborating with data science teams. The role requires statistical understanding, data analysis, Python experience, database familiarity, logical problem-solving, and the ability to communicate complex concepts clearly. It is designed for students nearing completion of degrees in mathematics, data science, statistics, actuarial science, or related fields.

The CX Tools & Automation Analyst will automate customer support tickets using APIs, optimize authentication methods, and enhance tooling efficiency while collaborating with stakeholders and documenting changes.

The Solutions Architect leads technical strategy for accounts, promoting data-driven transformation and adoption of Databricks' products while mentoring team members and engaging with clients.

As a Staff Engineer in Data Science, you will leverage your coding skills to tackle client challenges, guide teammates, and enhance solutions for greater success.

The Lead Data Scientist will design, develop, and deploy Machine Learning models, collaborate with teams to integrate solutions, and implement MLOps practices while providing mentorship and communicating findings effectively.