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LexisNexis (RELX)
LexisNexis (RELX)

Provides data and technology services, analytics, predictive insights, and fraud prevention for a wide range of industries.

Aprendiz - Ciência de Dados

职能数据科学
级别中级
地点Alameda Rio Negro; Brasil - São Paulo
方式现场办公
类型全职
发布1周前
立即申请

Principais responsabilidades:

  • Auxiliar na criação e atualização de relatórios e dashboards

  • Documentar processos, bases de dados e fluxos analíticos

  • Interagir com diferentes áreas para entender necessidades de dados

Requisitos:

  • Ensino médio completo ou cursando

  • Interesse em análise de dados e tecnologia

  • Perfil organizado, curioso e com vontade de aprender

Diferenciais:

  • Conhecimento básico em Excel

  • Conhecimento em ferramentas de visualização (Power BI, Tableau, etc.)

  • Familiaridade com conceitos básicos de estatística ou lógica de programação

Competências comportamentais:

  • Proatividade e vontade de aprender

  • Atenção a detalhes

  • Boa comunicação

  • Trabalho em equipe

  • Pensamento analítico

O que oferecemos:

  • Ambiente de aprendizado contínuo

  • Exposição a projetos reais de ciência de dados

  • Desenvolvimento técnico e comportamental

  • Acompanhamento próximo do time

  • Formato de trabalho flexível

  • Pacote de salário e benefícios

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关于LexisNexis (RELX)

LexisNexis (RELX)

Provides data and technology services, analytics, predictive insights, and fraud prevention for a wide range of industries.

10,001+

员工数

Alpharetta

总部位置

$41.2B

企业估值

评价

10条评价

4.0

10条评价

工作生活平衡

4.2

薪酬

2.8

企业文化

4.1

职业发展

2.9

管理层

3.2

72%

推荐率

优点

Great work-life balance and flexibility

Supportive and inclusive environment

Excellent benefits and health plans

缺点

Compensation and salary not competitive

Limited career advancement opportunities

Management communication issues

薪资范围

66个数据点

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Associate Data Scientist II

1份报告

$132,990

年薪总额

基本工资

$102,300

股票

-

奖金

-

$132,990

$132,990

面试评价

5条评价

难度

3.0

/ 5

时长

14-28周

体验

正面 0%

中性 80%

负面 20%

面试流程

1

Application Review

2

HR Screen

3

Technical Interview

4

Background Check

5

Offer

常见问题

Technical Knowledge

Past Experience

Behavioral/STAR

Data Analysis