Híbrido, en Heredia

This role involves working with large data sets to extract insights, build predictive models using AI and machine learning techniques, and deliver data-driven solutions to support key business decisions. The ideal candidate brings strong analytical thinking, technical proficiency in data science tools, and a continuous improvement mindset to help shape data strategy across the organization.

Key Responsibilities:

• Collect, clean, and preprocess structured and unstructured data from multiple sources.

• Build and maintain reliable data pipelines.

• Handle data quality issues such as missing values and inconsistencies.

• Conduct EDA to understand data trends, patterns, and relationships.

• Create visualizations using Tableau, Power BI, or similar tools to support business decisions.

• Apply ML algorithms (e.g., regression, classification, clustering, deep learning).

• Train, tune, and evaluate predictive models.

• Automate and optimize model deployment workflows.

• Use statistical and ML methods for forecasting, anomaly detection, and pattern recognition.

• Apply NLP and computer vision for specialized data types (text, image) as needed.

• Present complex data insights in a clear, actionable format to technical and non-technical stakeholders.

• Develop dashboards and performance reports for ongoing monitoring.

• Partner with stakeholders to understand business needs and deliver data driven recommendations.

• Translate analytical findings into strategic actions.

• Stay updated on trends in AI/ML, data analytics, and visualization.

• Automate processes and explore new tools to increase efficiency and accuracy.

Requirements:

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.

2–5 years of experience in data analysis or machine learning roles. Data preprocessing and pipeline development, Machine learning and model evaluation, Dashboard and visualization creation.

English advanced B2+ 85-90%

Strong programming skills in Python, R, or similar languages.

Proficient in SQL and comfortable working with large datasets.

Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch.

Expertise in data visualization tools like Tableau or Power BI.

Familiarity with cloud platforms (AWS, GCP, Azure).

Knowledge of AI techniques including NLP and deep learning

High attention to detail and accuracy. Self-motivated and adaptable. Effective time management and organizational skills. Strong analytical and problem-solving capabilities