Data Scientist

DYWIDAG; São Paulo; Presencial; BRL 160.000 - 200.000; Tempo integral

Resumo da oferta

Uma empresa líder em tecnologia de construção está em busca de um Data Scientist talentoso para se juntar à sua equipe em São Paulo, Brasil. O candidato ideal deve ter de 2 a 3 anos de experiência em ciência de dados, apoiando diversas funções com análises preditivas e o desenvolvimento rápido de produtos mínimos viáveis. As responsabilidades incluem coleta e análise de dados, desenvolvimento de modelos estatísticos e colaboração com equipes multifuncionais. Conhecimento em Power BI e ferramentas de visualização de dados é essencial.

Qualificações

• 2 a 3 anos de experiência comprovada como cientista de dados em ambiente empresarial.
• Especialização em modelos preditivos para motores de precificação e previsões de vendas.
• Experiência com ferramentas de visualização de dados, especialmente Power BI.

Responsabilidades

• Coletar, limpar e pré-processar dados estruturados e não estruturados.
• Desenvolver e otimizar modelos estatísticos e algoritmos de aprendizado de máquina.
• Prototipar rapidamente e entregar MVPs para atender a necessidades empresariais.

Conhecimentos

Análise de dados

Desenvolvimento de modelos preditivos

Programação em Python

Visualização de dados com Power BI

Trabalho em equipe

Formação académica

Bacharelado ou Mestrado em Ciência de Dados, Ciência da Computação, Estatística, Matemática ou área relacionada

Ferramentas

Power BI

Microsoft Azure

Python

R

SQL

Descrição da oferta de emprego

Data Scientist DYWIDAG • São Paulo, Brazil, Brazil

Descrição da vaga:

DYWIDAG stands as a global leader in construction and infrastructure technology that works with government authorities, asset owners, construction companies, and design offices to support their infrastructure projects. We have expanded into over 50 countries worldwide and continue to keep infrastructure safe and secure every single day.

Purpose of the Job

We are seeking a highly skilled and motivated Data Scientist to join our team. The ideal candidate will have 2–3 years of hands‑on experience as a data scientist in a business environment, supporting multiple departments and functions with predictive analytics and rapid development of minimal viable products (MVPs). A strong emphasis is placed on experience with pricing engines and sales forecasting solutions. You will be responsible for analyzing large datasets, building predictive models, and enabling data‑driven decision‑making across the organization.

Key Responsibilities

• Collect, clean, and preprocess structured and unstructured data from diverse sources.
• Develop, implement, and optimize statistical models, machine learning algorithms, and data mining techniques.
• Rapidly prototype and deliver MVPs to address business needs, especially in pricing and sales forecasting.
• Collaborate with the Global BI Team and cross‑functional stakeholders to understand requirements and translate them into actionable analytical solutions.
• Support various departments (e.g., Sales, Finance, Operations) with tailored predictive models and insights.
• Visualize data insights using dashboards and reports, primarily with Power BI.
• Clearly communicate findings and recommendations to stakeholders through presentations and documentation.
• Continuously improve data quality, analytical processes, and model performance.
• Stay current with the latest trends and technologies in data science, machine learning, and AI.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 2–3 years of proven experience as a data scientist in a business setting, supporting multiple departments/functions.
• Demonstrated expertise in developing predictive models for pricing engines and sales forecasting.
• Proficiency in programming languages such as Python, R, or SQL.
• Experience with data visualization tools, especially Power BI.
• Familiarity with Microsoft Azure cloud platforms is preferred.
• Strong problem‑solving skills and attention to detail.
• Excellent communication and collaboration abilities.

Preferred Qualifications

• Experience with big data technologies (e.g., Azure Data Factory, Synapse, Spark, Hadoop).
• Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
• Industry experience in Construction is preferred; experience in Manufacturing or Engineering‑related Big Data is also relevant.