Hybrid Senior Data Architecture Lead — AI & Biopharma

Takeda Pharmaceutical Co.; Ciudad de México; Híbrido; MXN 1.200.000 - 1.800.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

Annual bonus

Meal vouchers

Flexible working

Healthcare insurance

Time off

Descripción de la vacante

Takeda Pharmaceuticals invites you to join the Innovation Capability Center in Mexico City, where you will shape digital transformation and build AI-native assets for scientific workflows. You will work with data across drug discovery, preclinical development, CMC, and manufacturing to accelerate discovery, development, and manufacturing.

The role requires strong collaboration with scientists, product managers, and engineers to translate complex data into actionable outcomes, with a focus on

Formación

• PhD with +4 years in life sciences or Masters with +6 years or Bachelors with +8 years in industry.
• Proven track record in AI/ML driven use cases in cloud environments.
• Designed scalable and reusable data architecture.
• Experience collaborating with product managers, software engineers, and scientists.

Responsabilidades

• Drive product-minded, outcome-obsessed technical solutions for scientific data.
• Prototype, demo, and build to accelerate product delivery for end users.
• Collaborate with scientists and business leaders to maximize data value.
• Engage diverse audiences from scientists to executives with clear communication.
• Apply cutting-edge data methodologies to biopharma R&D pain points.

Educación

PhD

Masters

Bachelor

Descripción del empleo

Takeda Pharmaceuticals invites you to join the Innovation Capability Center in Mexico City, where you will shape digital transformation and build AI-native assets for scientific workflows. You will work with data across drug discovery, preclinical development, CMC, and manufacturing to accelerate discovery, development, and manufacturing.

The role requires strong collaboration with scientists, product managers, and engineers to translate complex data into actionable outcomes, with a focus on