Data Analyst

hace 6 días

San Francisco, Heredia, Costa Rica SPECTRAFORCE Costa Rica A tiempo completo

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:

Data Collection and Preparation


• 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.

Exploratory Data Analysis (EDA)


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


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

AI & Machine Learning Model Development


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


• Train, tune, and evaluate predictive models.


• Automate and optimize model deployment workflows.

Advanced Analytics


• 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.

Data Visualization & Reporting


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


• Develop dashboards and performance reports for ongoing monitoring.

Cross-functional Collaboration


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


• Translate analytical findings into strategic actions.

Continuous Improvement


• 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.

4–5 years of experience in data analysis, data cleansing, model evaluation, dashboard and visualization creation.

Verifiable knowledge in machine learning (AI techniques including NLP and deep learning)

English advanced B %

Ability to express the data analysis process, and to have logical reasoning

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).

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