Remote Technical Data Leader I

Daily Responsibilities:

• Lead the design, development, and implementation of advanced Machine Learning models, including neural networks, statistical, and mathematical models to solve complex business problems.
• Explore and actively apply the latest innovations in Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), and Agents to create cutting-edge solutions.
• Serve as a technical reference and mentor for the Data Science team, promoting professional development and knowledge sharing.
• Collaborate closely with multidisciplinary teams (Engineering, Product, Business) to identify opportunities, translate requirements into technical solutions, and ensure value delivery.
• Conduct complex data exploratory analyses, identifying patterns, trends, and actionable insights that guide strategic decision-making.
• Monitor and optimize the performance of implemented models in production environments, ensuring their robustness and efficiency.
• Research and propose the adoption of new technologies, tools, and methodologies in Data Science and AI.
• Define and obtain necessary datasets for analyses and modelings, as well as high-scale exploratory and productive environments.

What We're Looking For:

• A completed degree in Computer Science, Physics, Mathematics, Statistics, or related fields.
• Proven experience in building and implementing 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 leading, developing, and mentoring Data Science teams.
• Mastery of programming languages such as Python (with libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL.
• The ability to resolve complex problems analytically and creatively, 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 AI development and deployment.
• A portfolio of relevant projects in Data Science, especially with applications of GenAI and LLMs.
• Publishments or contributions to the Data Science/AI community.