Data Scientist

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

Resumo da oferta

A leading construction and infrastructure firm in São Paulo is looking for a skilled Data Scientist with 2–3 years of experience in predictive analytics and data modeling. The role involves working closely with various departments to deliver insights that drive decision-making. Candidates should have strong programming skills in Python, R, or SQL and experience with data visualization tools like Power BI. Familiarity with Microsoft Azure is preferred. This position offers opportunities for continuous improvement and staying current with data science trends.

Qualificações

• 2–3 years of proven experience as a data scientist in a business setting.
• Experience developing predictive models for pricing engines and sales forecasting.
• Proficient in programming languages such as Python, R, and SQL.

Responsabilidades

• Collect, clean, and preprocess structured and unstructured data.
• Develop and optimize statistical models and machine learning algorithms.
• Collaborate with cross-functional stakeholders to create analytical solutions.

Conhecimentos

Data analysis

Predictive modeling

Machine learning

Data visualization

Problem-solving

Collaboration

Formação académica

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics

Ferramentas

Python

R

SQL

Power BI

Microsoft Azure

Descrição da oferta de emprego

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.