ROLE DESCRIPTION
We are seeking a highly motivated and talented Applied Data Scientist to join our growing data science team. As an Applied Data Scientist, you will play a crucial role in translating complex business problems into actionable insights using advanced statistical modeling, machine learning, and data analysis techniques. You will work closely with cross-functional teams, including product, engineering, and business stakeholders, to identify opportunities, develop data-driven solutions, and drive impactful business outcomes. This role requires a blend of data science expertise and software engineering best practices to ensure models are robust, scalable, and maintainable.
RESPONSIBILITIES:
Develop and implement machine learning models and statistical analyses to solve real-world business problems, focusing on practical application and impact.
Collaborate with product managers and business stakeholders to understand business needs and translate them into data science projects.
Design and execute experiments to test hypotheses and validate model performance.
Build and maintain robust data pipelines for data ingestion, processing, and analysis, applying software engineering principles for reliability and efficiency.
Deploy and monitor machine learning models in production environments, ensuring performance and stability.
Write clean, well-documented, and testable code, adhering to coding standards and best practices.
Contribute to the development of our data science infrastructure, as well as occasional side projects outside of the traditional DS disciplines.
QUALIFICATIONS:
Degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Operations Research) or equivalent practical experience.
Experience with modeling libraries like CVXPy and Google OR-Tools.
Strong programming skills in Python with ability to write modular, object-oriented code, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
Proven experience in applying machine learning techniques (e.g., regression, classification, clustering, deep learning) to solve real-world problems.
Experience with data manipulation and cleaning using SQL and/or other data processing tools.
Experience with cloud platforms.
Strong problem-solving skills and a passion for data-driven decision-making.
BONUS POINTS:
Experience with Microsoft Azure.
Experience with CI/CD principles.
Experience with Docker/Kubernetes.
Experience with LLMs (OpenAI, Gemini).
Can communicate in Spanish.
