Data Scientist / AI Engineer – Analytics & AI Enablement

Genesis Studio LLC.; Teletrabalho; BRL 100.000 - 130.000; Tempo integral

Resumo da oferta

A leading digital solutions provider is seeking a Data Scientist with 3 to 5 years of experience in Data Science, Applied AI, or Analytics Engineering. The ideal candidate should be proficient in Python and SQL, possess strong analytical skills, and have familiarity with Azure-based platforms. This role involves collaborating with engineers to optimize datasets and build machine learning models. The position offers opportunities for professional development, remote work, and a comprehensive benefits package.

Serviços

Remote work model with flexible hours

Support for professional development

Health and life insurance

25 days of annual leave

Qualificações

• 3 to 5 years of experience in Data Science, Applied AI, or Analytics Engineering roles.
• Strong proficiency in Python for data analysis and modeling.
• Solid SQL skills for large-scale analytical datasets.
• Experience collaborating in data lakehouse or data warehouse architectures.
• Familiarity with Azure-based analytics and ML platforms.

Responsabilidades

• Collaborate with Data Engineers and stakeholders for data optimization.
• Document data requirements, feature definitions, and aggregation logic.
• Validate completeness and quality of serving-layer datasets.
• Build and test baseline machine learning models.
• Contribute to design and implementation of ML pipelines.

Conhecimentos

Data Science

Applied AI

Analytics Engineering

Python

SQL

Communication

Collaboration

Ferramentas

Databricks

Azure ML

Descrição da oferta de emprego

About Us

At Genesis Digital Solutions, we help companies innovate and thrive in the digital world. We are a team of technology and IT consulting specialists committed to excellence and making a real impact on our clients' projects. If you're looking for a dynamic environment where you can grow and contribute to cutting-edge technological solutions, we want to meet you!

What You Will Do

• Collaborate closely with Data Engineers and business stakeholders to define and validate curated datasets optimized for analytics and AI use cases.
• Specify and document data requirements, feature definitions, and aggregation logic for downstream analytical and machine learning applications.
• Validate data completeness, consistency, and statistical soundness of serving-layer datasets.
• Provide continuous feedback to data engineering teams on data model usability, performance, and analytical fitness.
• Perform exploratory data analysis (EDA) to identify patterns, anomalies, and data quality issues.
• Build and test baseline machine learning models and analytical prototypes using curated datasets.
• Contribute to the design and implementation of lightweight ML pipelines (training, evaluation, inference) aligned with platform standards.
• Ensure features and models are reproducible, versioned, and prepared for future operationalization in production environments.

What We Are Looking For

• 3 to 5 years of experience in Data Science, Applied AI, or Analytics Engineering roles.
• Strong proficiency in Python for data analysis and modeling (e.g. pandas, numpy, scikit-learn or equivalent).
• Solid SQL skills for working with large-scale analytical datasets.
• Experience collaborating with Data Engineers in data lakehouse or data warehouse architectures.
• Familiarity with Azure-based analytics and machine learning platforms (e.g. Databricks, Synapse, Azure ML).
• Awareness of data quality, governance, and privacy considerations in analytical workflows.
• Strong analytical mindset with attention to data validity, assumptions, and statistical robustness.
• Ability to translate business and product questions into clear data and feature requirements.
• Strong communication skills and a collaborative working style with technical and non-technical stakeholders.
• English level B2 or higher (mandatory)

What We Offer

• A workplace that values innovation and personal growth.
• Opportunities to work on high-impact projects.
• Remote work model with flexible hours.
• Support for professional development, including training and certifications.
• Health and life insurance.
• 25 days of annual leave.