📍
Rio de Janeiro, Brazil

Data Scientist - STUDENT CONVERSION

No experience
Technology & Digital
Data / Analytics
Posted:
December 29, 2025

IBM

Global technology company
72.1
Palpable Score
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Your role and responsibilities

Como Associate na IBM, você trabalhará para solucionar problemas de negócios usando ferramentas de ponta e de código aberto, como Python, R e TensorFlow, combinadas com ferramentas da IBM e nossos pacotes de aplicativos de IA. Você preparará, analisará e compreenderá dados para gerar insights, prever tendências emergentes e fornecer recomendações às partes interessadas. Em sua função, você poderá ser responsável por:

Required education

Associate's Degree/College Diploma

Preferred education

Technical Diploma

Required technical and professional expertise

About the company

IBM

Company overview
IBM is a global technology company that sells software, consulting services, and infrastructure products to large organisations. IBM’s current focus areas include hybrid cloud, AI, cybersecurity, automation, and enterprise IT modernisation. IBM also operates a large consulting arm that delivers transformation programmes for clients across industries. IBM works with customers worldwide, from governments and banks to retailers and manufacturers.

Locations and presence

IBM operates globally with offices and client sites across North America, Europe, Asia-Pacific, and other regions, with headquarters in Armonk, New York. Working patterns vary by role and business unit, and public reporting shows IBM has required in-office or client-site presence (often at least three days a week) for some groups such as US managers and parts of the sales organisation.

Palpable Score

72.1
/ 100
IBM is a strong early-career option for people who want multiple entry doors, because IBM runs internships, apprenticeships, and named entry-level programmes alongside “entry level” job hiring. IBM is also more transparent than many large tech employers about the steps in the hiring process and how assessments work, including accommodations and asking for feedback. The main constraints are uneven pay transparency by country and role, plus limited public outcome data (conversion rates, promotion timelines) for early-career cohorts.
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