Data Scientist E Machine Learning Engineer
2 semanas atrás
A área de Data Science dedica-se à análise e modelação de dados resolvendo problemas diversos e multidisciplinares com auxílio de conhecimentos de diversas áreas (matemática, engenharia de software e o conhecimento de algoritmos de machine learning). O nosso foco está na implementação de soluções com impacto e que gerem valor. Com isso em mente, existe um grande foco nas nossas metodologias de desenvolvimento e abordagem aos problemas. Python é a principal linguagem de programação sendo sempre que necessário aplicada de forma distribuída permitindo a implementação de soluções em escala.
Quais as principais responsabilidades?
Enquanto Data Scientist , terás a oportunidade de resolver problemas do mundo real em algumas das principais indústrias (Educação, Ciência, Banca, Telecomunicações e Distribuição). Terás como missão aplicar diversas técnicas de data science tais como treino e modelação de modelos preditivos e análise e visualização de dados a problemas específicos destas áreas da sociedade com a finalidade de obter informação de valor a partir da extração, preparação e manipulação de grandes quantidades de dados.
Diariamente serás responsável por:
Implementar soluções para extração, transformação e padronização de dados que transformem dados em bruto em informações inteligíveis e relevantes;
Pesquisar, analisar e implementar algoritmos modernos e eficientes a fim de fazer o melhor uso do conjunto de dados em análise;
Realizar análises exploratórias de dados e elaborar relatórios baseados nos dados e que permitam retirar conclusões a partir dos mesmos;
Otimização de soluções globais com recurso a modelos de machine learning/informação criada por análise de dados.
Stacks: Python/PySpark, R
Que Skills precisas de ter?
Licenciatura e/ou Mestrado em Informática e Computadores, Sistemas de Informação, Matemática, Ciência da Computação ou uma área similar;
Experiência mínima de 1 ano em funções de Data Scientist;
Conhecimentos de SQL, manipulação de dados e técnicas de visualização;
Experiência de programação em Python em particular na utilização de bibliotecas de cariz matemático e de machine learning (NumPy, SciPy, scikit-learn, pandas, Keras, TensorFlow, PyTorch, PySpark);
Conhecimentos ou experiência em técnicas de machine learning supervisionadas e não supervisionadas;
Conhecimentos de algoritmos de data mining e reconhecimento de padrões;
Paixão pela exploração dados, pela sua preparação e conversão (bruto -> legíveis -> engenharia e funcionalidades);
Boa capacidade de comunicação e facilidade em trabalhar em equipa, com foco na resolução de problemas complexos;
Fluente em Inglês (escrito e falado).
Pontos extra para:
Experiência em Microsoft Azure, GCP e/ou AWS;
Conhecimento de estatística e conceitos matemáticos tais como regressões lineares e logísticas, distribuição de dados e testes de normalidade.
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