Cientista de Dados Sênior

About the role

Join the Data Science team at C6 Bank to transform data into business decisions. You will develop analytical solutions, models, and data products that directly impact the company and its customers. This role involves the full lifecycle of initiatives, from problem identification to implementation and evolution of solutions in production. You will collaborate with business stakeholders, data engineering, and technology teams to ensure that data-driven strategies are aligned with the bank's objectives. The position requires a strong scientific methodology to approach challenges and contribute to the continuous improvement of analytical products. You will be responsible for delivering robust and scalable solutions that drive measurable business value. This is an opportunity to work in a dynamic environment where data integrity and technical excellence are highly valued.

Key facts

What you'll do

• Develop solutions for banking products, collaborating with business, data engineering, and technology teams to ensure alignment with strategic goals.
• Create, test, and deploy end-to-end machine learning solutions that are robust, scalable, and maintainable in production environments.
• Analyze data to validate hypotheses and generate valuable business insights that support decision-making processes across the organization.
• Clean, process, and explore data from various sources to ensure high-quality datasets suitable for advanced analytical modeling.
• Build and maintain data pipelines and models in production, ensuring quality, reliability, and performance under real-world conditions.
• Contribute to team code, documentation, and technical discussions, offering methodological and scientific expertise to elevate the overall standards of the group.
• Apply statistical modeling and machine learning algorithms to solve complex business problems and identify opportunities for optimization.
• Translate business problems into analytical solutions by defining metrics, experiments, and frameworks to measure success and impact.
• Partner with cross-functional teams to gather requirements, define project scopes, and ensure that deliverables meet business and technical expectations.
• Mentor and support junior team members by sharing knowledge, best practices, and techniques to foster a culture of continuous learning.
• Evaluate new tools, libraries, and methodologies to assess their applicability and potential benefits to the data science initiatives within the bank.
• Ensure that all analytical processes adhere to data governance, security, and compliance standards established by the organization.

Requirements

• Substantial experience as a Data Scientist, with a history of deploying models into production and managing their lifecycle in real-world scenarios.
• Proficiency in Python for data analysis and machine learning, including the ability to write clean, efficient, and well-documented code.
• Experience with statistical modeling and machine learning algorithms, including supervised and unsupervised learning techniques.
• Strong ability in exploratory data analysis (EDA) and translating business problems into analytical solutions that provide actionable insights.
• Knowledge of SQL and handling large data volumes, including query optimization and performance tuning for complex datasets.
• Familiarity with engineering best practices such as Git, testing, organized code, and version control to ensure reproducibility and maintainability.
• Excellent communication skills for both technical and non-technical audiences, enabling effective collaboration and clear articulation of complex concepts.
• Demonstrated capacity to work independently and as part of a collaborative team, contributing to a positive and productive work environment.
• Commitment to maintaining high standards of data quality, model accuracy, and ethical considerations in the application of data science practices.
• Willingness to continuously update technical skills and stay current with advancements in data science, machine learning, and related fields.

Nice to have

• Experience in the financial sector or regulated environments, providing context-specific insights into industry challenges and best practices.
• Knowledge of MLOps and model monitoring, including tools and frameworks that ensure the reliability and performance of deployed models.
• Experience with CRM systems, understanding how customer data can be leveraged to drive personalized experiences and business growth.
• Willingness to work in person, contributing to the team's collaboration and engagement within the office environment.

Practical notes

The role operates on a full-time basis, with expectations for collaboration during standard business hours in São Paulo. While the position is primarily based in the office, considerations for remote or hybrid arrangements may be evaluated on a case-by-case basis. Travel is not a requirement for this role, as the responsibilities are focused on local execution and collaboration within the São Paulo office. Candidates must be authorized to work in Brazil, and prior experience with local regulations is advantageous. The selection process will include technical assessments, interviews, and evaluations of past project contributions. Deadlines for application submission are not specified, interested candidates should submit their profiles as soon as possible to be considered for the upcoming hiring cycle.