Data Scientist – Senior Consultant

Data Scientist – Senior Consultant - Americas Delivery Mexico (ADMX)

Are you an experienced, passionate pioneer in technology? A Data Scientist who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. Americas Delivery Mexico (ADMX) leverages scale and talent to provide high quality, cost-effective service to our clients.

ADMX is a member of the Global Delivery Network which has presence across the world with Delivery centers in the United States, Romania, India, Spain, China, and the Philippines. ADMX is in Queretaro, Mexico. We provide consulting services to help our clients achieve a higher level of service in operational efficiency and business value. We are a team of professionals passionate about serving clients with distinction and learning, and we are driven by our purpose: Making an impact that matters for our clients, our people, and society.

Work you’ll do/Responsibilities

As a Senior Consultant, you will work with diverse global clients across a wide range of industries. You will have a variety of client facing responsibilities such as diagnosing issues using advanced analytical techniques, interviewing staff, formulating and making recommendations, and helping clients implement proposed solutions.

• Leads the design and delivery of advanced analytics and AI/ML solutions on complex client engagements. Owns the analytical architecture within a workstream, drives cross-team alignment, and serves as a trusted advisor to client stakeholders. Actively contributes to practice growth, proposals, and talent development.

• Architects end-to-end AI/ML solutions including feature stores, model training platforms, serving infrastructure, and monitoring systems.

• Defines the analytics strategy and roadmap for client data science capabilities.

• Leads cross-functional collaboration between data science, data engineering, and software engineering teams.

• Designs and implements enterprise-grade MLOps practices, including CI/CD for models, drift detection, and retraining pipelines.

• Engages client stakeholders at Director/VP level; presents solution options with trade-offs and business impact.

• Contributes to BD activities with solution design, estimation, and staffing recommendations.

• Mentors Analysts and Consultants through structured feedback, pairing, and internal knowledge sharing.

The Team

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You’ll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to business. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure.

These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Qualifications

Required

• 6-10+ years of consulting and/or industry experience

• Completion of course of study/Egresado in Computer Science/IT/Computer Engineering, or any pertinent field or industry, or equivalent years of experience

• Responsible for supporting and leading project workstreams and/or teams

• Identifies key drivers, defines problems and proposes solutions

• Advanced English level

• Python Expert; designs scalable ML frameworks and internal accelerators; optimizes for performance and reliability; contributes to open-source or internal libraries.

• BI / Analytics: Designs enterprise analytics platforms; defines semantic models, KPI frameworks, and data products; aligns BI strategy with business objectives.

• Cloud AI (AWS/GCP/Azure): Multi-cloud experience; holds or working toward AI/ML cloud certifications; architects cost-optimized, scalable, and secure AI workloads.

• ML / Modeling: Expert across multiple modeling domains (NLP, CV, forecasting, recommendation systems); designs responsible AI frameworks (fairness, explainability, bias).

• Statistics: Expert in applied statistics; leads experiment design, causal analysis, and uncertainty quantification at enterprise scale.

Applicants m