Data Science Director

hace 6 días

Xochimilco, México Global Institute for Digital Competitiveness A tiempo completo

Diversity & Equality_

Likewise, we believe in respect for Human Rights and do not discriminate against any program, activity or person for reasons of sexual preference, economic income, religious preference, race, belief, Color, Nationality, Age, Gender or Disability.

**_Job description_**

We are looking for a Global Data Science Head Director. This person will lead a best-in-class data science team with 3 key goals:
1. To build our Global Data Science Center Delivery.

2. To develop a portfolio of high-stakes,

3. Impactful machine learning and data-driven intelligent products, and to define and innovate cross-functional AI/ML capabilities at scale across Horizones functions, in collaboration with other teams and leaders of our Global Institute for Digital Competitiveness (ie. AI proof-of-value, Blockchain, tools & ethical framework)

If you have experience in Consultancy companies like Bain, Mckinsey, BCG, Deloitte, PWC, EY, KPMG, Accenture, Capgemini, Softtek, Cognizant this your opportunity to build with us our Global Data Science Center Delivery
- **Experience & Qualifications**_
- 12+ years of hands-on experience working in Data Science / Big Data / Machine Learning
- 5+ years of experience in effectively managing data science teams (10-30 people)
- 5+ years’ experience in designing and implementing AI solutions in public cloud (AWS, GCP, or Azure)
- 5+ years’ experience in designing and implementing AI solutions in public cloud (AWS, GCP, or Azure)
- Experience of a programming language such as R, Python, or Scala and one coding environment such as Jupyter notebook
- Knowledge of some of the popular ML frameworks such as TensorFlow, Pytorch Keras, SparkML, scikit-learn, XGBoost, H2O
- Experience with large scale DL model training using one of the common frameworks such as PyTorch or TensorFlow/Keras
- Knowledge of advanced NLP solutions in one or more of: Named Entity Recognition, Document Classification, Document Summarization, Cognitive Data Extraction, Sentiment Analysis, Conversational agents
- Experience in feature extraction techniques and implementation of ML pipeline automation
- Experience with AI Ops design and implementation
- Familiar with tools & techniques enabling dimensions of Responsible AI, such as Explainability, Fairness, Privacy
- Proficiency in container technologies (Kubernetes, Docker, etc.),
- Experience with Big Data technologies
- Understanding and knowledge of DevOps tools and (CI/CD) frameworks
Tipo de puesto: Tiempo completo, Por tiempo indeterminado

Horario:

- Turno de 8 horas

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