About this role
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Day-to-day responsibilities: Lead the design, development and implementation of advanced Machine Learning models, including neural networks, statistical and mathematical models to solve complex business problems. Actively explore and apply the latest innovations in Generative Artificial Intelligence (GenAI), Large Language Models (LLMs) and Agents to create cutting-edge solutions. Act as a technical reference and mentor for the team of Data Scientists, promoting professional development and knowledge exchange.
Collaborate closely with multidisciplinary teams (Engineering, Product, Business) to identify opportunities, translate
Requirements
into technical solutions and ensure value delivery. Conduct exploratory analysis of complex data, identifying patterns, trends and actionable insights that guide strategic decision-making. Monitor and optimize the performance of models implemented in a production environment, ensuring their robustness and efficiency.
Research and propose the adoption of new technologies, tools and methodologies in Data Science and AI. Define and have the ability to obtain necessary datasets for analysis and modeling and high-scale exploratory and productive environments.
What We are Looking For
: Complete higher education in Computer Science, Physics, Mathematics, Statistics or related areas. Proven experience in construction and implementation of machine learning models, including neural networks, statistical and mathematical models. In-depth knowledge and practical experience with GenAI, LLMs and Agents.
Experience in Data Engineering, including pipeline design, ETL/ELT and database optimization. Experience in training, development and technical leadership of Data Science teams. Proficiency in programming languages such as Python (with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL.
Ability to solve complex problems in an analytical and creative way, with a results-oriented approach. Excellent communication, leadership and interpersonal skills, with the ability to influence and collaborate at different levels of the organization. Proactivity, curiosity and passion for continuous learning.
Differentiators: Experience with Big Data tools (e.g. Spark, Hadoop, Kafka). Solid knowledge in Data Engineering, including pipeline design, ETL/ELT and database optimization.
Knowledge of cloud platforms (AWS, GCP, Azure) for development and deployment of AI solutions.Portfolio of relevant projects in Data Science, especially with GenAI applications and LLMs.Publications or contributions to the Data Science/AI community. This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.
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