• Closely work with the AI Lead to define organizations and customers vision, roadmap, and priorities for AI adoption and integration.

• Evaluate business needs and identify high-value AI opportunities across functions.

• Explore new AI tools, technologies, and industry trends to ensure the organization stays ahead.

• Develop, train, and optimize machine learning models using state-of-the-art algorithms and techniques.

• Process and analyze large datasets to extract meaningful features and insights.
• Build scalable ML pipelines and deploy models into production environments.
• Collaborate with data scientists, telco engineers, automation experts and product managers to understand business requirements and translate them into AI solutions.
• Monitor model performance and continuously improve accuracy, efficiency, and robustness.
• Stay updated on emerging AI/ML trends and tools to apply best practices.
• Document experiments, processes, and results clearly for knowledge sharing and reproducibility.
• Use traditional automation languages like python combined with ML models to create a final product beneficial for Network Planning and Optimization practices. Python practical experience is a must

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The Data Science and AI specialist is responsible for designing and delivering AI-driven solutions that optimize network performance and operations. This role involves identifying high-value AI use cases across radio, core, and transport networks; architecting data pipelines, models, and automation frameworks; and ensuring seamless integration with existing NPO tools and platforms. In this pivotal role, you'll partner closely with engineering, product, and operations experts, transforming complex business and network challenges into powerful, scalable AI solutions. Your work will directly enhance efficiency, elevate forecasting, refine anomaly detection, optimize performance, and enrich customer experiences. You'll also responsible for data quality and AI, overseeing the end-to-end implementation and continuous refinement of models that drive advancements in 5G, 6G, ORAN, and automation initiatives."

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• Bachelor’s or master’s degree in data science, Computer Science or related fields.
• A minimum of 12+ years of industry standard experience, 6-7 years work experience in software development/engineering projects, with minimum 2-3 years of AI/ML & Data Engineering experience.
• Strong programming skills in Python and familiarity with ML libraries.
• Experience with data manipulation and transformation, big data queries and handling larger datasets.
• Understanding of ML algorithms including supervised, unsupervised, and deep learning methods.
• Experience in interfacing python tools with relational databases – Atleast 1-2 of these (Clickhouse, Presto, MySQL, Oracle, SQL Server, Postgress)
• Solid foundation in statistics and data analysis.
• Knowledge of cloud platforms (AWS, GCP, Azure) and experience with containerization (Docker, Kubernetes) is a plus.
• Strong problem-solving skills and ability to work independently and collaboratively.
• Excellent Communication skills – English.
• Spanish and Portuguese is a plus - Optional.
• Good knowledge of 5G & LTE network architecture, and network optimization is a plus – Optional

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Interprets internal and external business challenges and recommends best practices to improve products, platforms, tools, processes and services using AI & Automation initiatives.

• Has in-depth organisational and relevant market knowledge and uses understanding on how relevant areas can be integrated to achieve objectives.

• Solves complex problems based on sophisticated analytical thought and complex judgment.

• Contributes to development of concepts to determine professional direction of own organisational unit.

• Develop, train, and optimize machine learning models using state-of-the-art algorithms and techniques.
• Process and analyze large datasets to extract meaningful features and insights.
• Build scalable ML pipelines and deploy models into production environments.
• Collaborate with data scientists, telco engineers, automation experts and product managers to understand business requirements and translate them into AI solutions.
• Monitor model performance and continuously improve accuracy, efficiency, and robustness.
• Stay updated on emerging AI/ML trends and tools to apply best practices.
• Document experiments, processes, and results clearly for knowledge sharing and reproducibility.
• Use traditional automation languages like python combined with ML models to create a final product beneficial for Network Planning and Optimization practices.