Top Data Science Jobs in Mexico

Analyzes workforce and healthcare data to identify trends, build predictive and machine learning models, and deliver actionable recommendations. Uses Python, Alteryx, and Power BI for analytics, visualization, and reporting. The role supports workforce strategy, employee engagement, organizational effectiveness, talent management, and healthcare cost insights. Responsibilities also include client collaboration, relationship management, team guidance, and applying risk adjustment and medical economics concepts to inform strategic decisions.

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.

The Sr Director leads the development, strategy, and commercialization of Credit Risk Solutions in Mexico, overseeing product innovation and managing cross-functional teams.

Own the acquisition product roadmap and engineering priorities to drive durable user growth. Define target audiences and channel mix, build product-driven acquisition mechanics (referrals, growth loops), enable channel effectiveness (discoverability, search/AI readiness, integrations, tracking), test new acquisition tactics, and align product investment with Performance Marketing, SEO, Partnerships, and Brand while measuring long-term subscriber value.

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 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 Scribd’s content intelligence and UGC supply portfolio, owning corpus classification, metadata, quality, gap analysis, AI infrastructure, contributor experiences, and content acquisition strategy. Partners with ML, engineering, data science, consumer product, and business development teams to connect content supply with business value. Manages senior product leaders and established engineering and analytics programs while setting portfolio roadmaps and representing content strategy with executives.

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.

Lead the development, validation, and maintenance of clinical data programming solutions for EDC/CDMS systems, vendor data, analytics, reports, integrations, and data transfers. Provide technical leadership across studies, serve as a programming subject matter expert, mentor programmers, support study teams, and drive automation and process improvements. Collaborate with data managers, biostatisticians, and project managers to ensure high-quality clinical trial data management solutions.

Build and deploy statistical and ML models (especially demand forecasting) to improve sales forecast accuracy. Analyze data, create actionable insights, collaborate with stakeholders and regional teams, set analytics standards, monitor model performance, and deliver dashboards and visualizations for supply chain decision-making.

Lead data science and Generative AI initiatives using AWS Bedrock, foundation models, and LLMs. Provide production support, incident management, root-cause analysis, modernization, solution design, proof-of-concept development, high-quality Python coding, code reviews, testing, deployment, monitoring, documentation, and ongoing feature and defect maintenance. Collaborate with distributed teams and follow architectural decisions and agile delivery practices.

Leads end-to-end clinical data review and delivery activities across studies, ensuring quality, timeliness, budget adherence, and data fitness for analysis. Oversees analytic review, clinical system development input, risk management, planning, resourcing, and audit participation. Serves as the primary contact for internal and external stakeholders, manages multiple projects, and provides leadership, mentoring, and subject matter expertise. The role requires approximately 15% domestic or international travel.

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.

Leads clinical data science programming for clinical trials, including EDC/CDMS solutions, data validation, analytics, risk management outputs, custom reports, vendor data handling, data transfers, and system extracts. Collaborates with cross-functional teams, serves as a programming subject matter expert, mentors programmers, supports training and knowledge sharing, and improves technical systems and processes.

The Promoter Agencies Manager will oversee field marketing agencies to drive customer engagement and sales through a national demand generation strategy. Responsibilities include managing agency relationships, analyzing marketing metrics, and coordinating marketing initiatives.

ICON is seeking clinical data science professionals across Latin America with experience in clinical data management, clinical systems, data standards, risk management, analytics, or related areas. Responsibilities and opportunities will vary across current and future roles. Candidates should understand clinical trial processes and data flows, demonstrate strong analytical skills and attention to detail, and value quality, innovation, and continuous learning.

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.

Responsible for creating and maintaining brand- and item-level consensus depletion forecasts by partnering with Marketing, Innovation, Finance and Operations. Translate portfolio and innovation plans into demand outlooks, quantify demand drivers and risks, apply statistical modeling and analytics, present forecast recommendations, and drive cross-functional alignment and continuous improvement in demand planning processes.

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.

Lead technical strategy and execution for production clinical AI across a portfolio: set AI direction, ensure regulatory and governance alignment, partner with product and engineering, improve model evaluation/monitoring and production reliability/cost/latency, promote reusable model patterns, and hire/coach data science leaders to scale clinical AI capabilities.

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

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.

Teach and mentor Data Science bootcamp students: lead live lessons and Q&As, provide 1:1 video support, answer messages, review projects, give actionable feedback, troubleshoot code, and share industry best practices. Full-time remote role supporting learners throughout the program.