Cientista de Dados Especialista II - Mensuração
New
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLGCPGitMachine LearningA/B testing
Requirements
- Strong proficiency in Python for data analysis and SQL for data manipulation and querying.
- Advanced knowledge of statistics, including hypothesis testing, probability distributions, sample size calculations, statistical significance, and experimental design.
- Hands-on expertise with causal inference techniques such as Synthetic Controls, Difference-in-Differences, and other methodologies for impact measurement.
- Solid experience designing and implementing A/B testing frameworks and experimentation methodologies.
- Proven experience developing, evaluating, and interpreting machine learning models and performance metrics.
- Strong analytical, critical thinking, and problem-solving skills with the ability to independently lead complex projects.
- Experience with version control tools such as Git and cloud environments, particularly Google Cloud Platform (GCP).
- Proficiency with AI-powered development tools and coding assistants to accelerate productivity and documentation processes.
- Ability to gather business requirements, translate them into technical solutions, and work autonomously in multidisciplinary environments.
- Excellent communication and stakeholder management skills, with a strong interest in understanding business processes and portfolio management challenges.
Responsibilities
- Design, execute, monitor, and measure complex A/B tests and business experiments, ensuring statistical rigor and reliable decision-making.
- Develop and monitor sales performance indicators and analytical solutions aimed at improving portfolio profitability and optimization.
- Build descriptive, predictive, and prescriptive data science models to support resource allocation, process optimization, and strategic portfolio decisions.
- Lead end-to-end data science initiatives, including business understanding, feature engineering, modeling, validation, deployment support, and impact measurement.
- Apply causal inference methodologies to accurately estimate the incremental impact of business initiatives and avoid analytical biases.
- Collaborate closely with business stakeholders to define requirements, translate business challenges into analytical solutions, and monitor model performance.
- Contribute to the evolution of data products and measurement frameworks that support portfolio health and performance management.
- Promote best practices in experimentation, analytics, and data-driven decision-making across multidisciplinary teams.
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