Localiza&Co

Junior Data Scientist

Localiza&Co

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇧🇷 Brazil

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Job Level

Junior

Tech Stack

AWSDockerKubernetesPythonSQL

About the role

  • Propose, design, and develop end-to-end robust, scalable, and high-performance machine learning models;
  • Develop recommendation models and journey personalization solutions;
  • Define cases/hypotheses and conduct high-quality analyses, extracting insights and value from data;
  • Propose, develop, and implement monitoring and measurement solutions for results;
  • Develop and implement optimized solutions for large-scale data processing;
  • Assist and support other data scientists in data analysis and model development.

Requirements

  • Experience deriving value from data, preferably in Data Science and AI;
  • Strong ability to present methodologies and results to business stakeholders;
  • Knowledge of Machine Learning algorithms and Data Mining;
  • Experience with statistics and databases;
  • Solid knowledge of Python and SQL;
  • Knowledge of Data Visualization;
  • Ability to work effectively in a team.
  • **PREFERRED QUALIFICATIONS:**
  • Experience developing models on AWS;
  • Experience developing pricing models;
  • Experience developing recommendation models;
  • Experience with generative models / generative AI;
  • Familiarity with SageMaker (AWS);
  • Experience with Docker and Kubernetes.
Benefits
  • Profit sharing
  • Food allowance
  • Meal allowance
  • Health insurance
  • Dental insurance
  • Gympass
  • Private pension plan
  • Home office allowance
  • Allya
  • Unlimited access to a variety of courses from our Localiza University
  • Internal training and development programs
  • Discounts on vehicle purchase and rental

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningrecommendation modelsdata analysisdata processingPythonSQLstatisticsdata miningdata visualizationgenerative models
Soft skills
presenting methodologiesteamworkcommunication