AI-Driven Data & Analytics Solutions Architect

3502 Servicios Internacionales De Atencion Al Cliente, Limitada; Región Centro; Híbrido; MXN 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

Genpact is seeking a Solution Architect - Data and Analytics to design scalable ML and data solutions in a fast-moving environment. You will work with business partners to shape use cases like predictive quality, yield, and anomaly detection, and define end-to-end ML solution architecture including data pipelines, training, and deployment.

You will lead MLOps practices, model evaluation, and cost-aware design, ensuring robust, scalable solutions aligned with business needs.

Formación

• Four related bachelor degrees are required in analytics and computing fields.
• Master’s in Data Science adds advanced knowledge for modeling and data science work.
• Industry certifications supporting data management and architecture are listed in the ad.

Responsabilidades

• Use cases and solution design for data and analytics initiatives.
• Collaborate with business and plant experts to prioritise use cases such as predictive quality and process optimisation.
• Define ML solution architecture including data pipelines, training, deployment, and integration with product APIs.
• Define MLOps, tracking, CI/CD for models, monitoring, and drift detection.
• Set evaluation standards and manage compute and storage to ensure scalable, reliable solutions.

Conocimientos

Big Data Solutions

BI

Cloud Computing

Collaboration Tools

Database Management

Data Integration

Data Management

Master Data Management

Metadata Management

Solution Architecture

Educación

Bachelor's - Business Analytics

Bachelor's - Computer Science

Bachelor's - Statistics

Master's - Data Science

Descripción del empleo

Genpact is seeking a Solution Architect - Data and Analytics to design scalable ML and data solutions in a fast-moving environment. You will work with business partners to shape use cases like predictive quality, yield, and anomaly detection, and define end-to-end ML solution architecture including data pipelines, training, and deployment.

You will lead MLOps practices, model evaluation, and cost-aware design, ensuring robust, scalable solutions aligned with business needs.