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IBM

Data Analyst

IBM

Published 13 May 2026
Heredia, Costa Rica
Full Time

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Role Highlights

Languages used

SQL
Python

Key skills

Machine Learning
Data Visualization
Supply Chain Management
Cloud
AI
Modelling
Optimization
Statistics

Tools, Libraries and Frameworks

IOS
Red Hat
IBM
Plotly
Matplotlib
Seaborn

Description

The role involves leveraging data and analytics expertise to address complex business challenges. The individual will develop predictive models using mathematical optimization and simulation techniques to forecast trends. Responsibilities include managing diverse data structures to support data-driven decision-making and business optimization. The professional will implement data visualization to communicate insights effectively to stakeholders. Furthermore, the role requires applying machine learning and statistical modeling to solve problems in areas such as supply chain management and risk assessment.

Required Qualifications and Skills

The role requires proficiency in SQL and Python for data analysis tasks. Candidates must demonstrate the ability to work independently on assigned data with minimal daily input. The position necessitates the capability to manipulate raw data sources to generate actionable business insights. No specific degree or professional qualifications are mentioned in the text.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

IBM

Size

305978

Website

ibm.com

HQ

Armonk, New York, US

Public/Private

Public Company

Description

IBM infuses core business operations with intelligence, from machine learning to generative AI, to make organizations more responsive, productive, and resilient. It helps clients put AI into action now, creating real value with trust, speed, and confidence across various areas like digital labor, IT automation, and security. The ability to utilize all data is critical, as AI's effectiveness is dependent on the quality of data fueling it, with IBM's AI, and data platform aiming to scale and accelerate AI's impact with trusted data. IBM's hybrid cloud platform offers a comprehensive approach to development, security, and operations across hybrid environments, laying a flexible foundation for leveraging data wherever it resides.

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