DATA SCIENTIST III | DATA ENGINEERING & SCIENCE
About this role
Conducting exploratory data analyses on large transactional datasets and building machine learning models for fraud detection, credit risk, and recommendation systems forms the core of daily responsibilities. Team members operate within the Data Science division to transform high volumes of information into predictive models and strategic insights, acting as senior technical references for the group. Individuals joining this environment handle end-to-end data science projects from conception to production while mentoring junior and pleno colleagues.
Inter Carreiras structures the organization around a global financial super app ecosystem, challenging technical staff to scale solutions that impact millions of users. Successful candidates combine robust machine learning expertise with strong collaboration skills, bridging the gap between product owners, software engineers, and analytics teams to evolve the corporate data culture.
What you will do
- Conduct exploratory data analyses on large transactional and behavioral datasets to uncover actionable business opportunities.
- Build and implement machine learning and deep learning models for fraud detection, credit risk analysis, recommendation systems, churn prediction, and propensity modeling.
- Validate hypotheses using controlled experiments, A/B testing methodologies, and statistical analysis.
- Lead end-to-end data science projects from initial design through production deployment.
- Act as a technical reference within the team by guiding junior and pleno data scientists through code reviews and technical mentoring.
- Collaborate closely with product owners and engineers to translate business challenges into scalable analytical solutions.
- Contribute to the definition of engineering best practices, technical standards, and data culture evolution.
What you need
- Demonstrate solid professional background in deploying machine learning models into large-scale production environments with proven business impact.
- Show proficiency in Python utilizing core libraries such as pandas, numpy, matplotlib, scikit-learn, and PyTorch.
- Apply advanced SQL capabilities to query and manipulate large volumes of data efficiently.
- Utilize Apache Spark for distributed processing of massive datasets.
- Incorporate AWS cloud services such as S3, SageMaker, Glue, or EMR for developing and deploying data solutions.
- Manage code versioning and collaboration workflows using Git.
- Possess a strong foundation in descriptive and inferential statistics, probability, and hypothesis testing.
- Communicate technical results clearly to diverse audiences through data storytelling and maintain familiarity with MLOps principles.
Nice to have
- Experience in developing machine learning solutions in production environments
- Experience with Apache Airflow for data pipeline orchestration
- Experience with A/B testing methodologies in digital product environments
- Background in technology companies or high-volume fintechs
- Experience in technical leadership or data team mentorship
- Knowledge of feature stores, model monitoring tools like MLflow, and advanced MLOps practices
- Intermediate or advanced English proficiency
Benefits
- Vale-alimentação e Vale-refeição
- Plano de saúde e odontológico
- Seguro de vida
- DayOff de Aniversário
- Baby On Board e Sala de Amamentação
- Licença parental estendida
- Auxílio-creche/babá e/ou auxílio para filhos com deficiência
- Wellhub e Grupo de Corrida Inter
- Espaço CARE4U
- Vantagens no nosso SuperApp, como Duo Gourmet Cartão Prime Inter
- Programas de treinamento e capacitação internos
Skills and tech stack
Questions candidates ask
What does the selection process look like?
The hiring process consists of resume screening, an initial screening call for expectation alignment, assessments, a talent team interview, a technical test when necessary, a leadership interview, and finally a job offer.
What tools and technologies will I use?
You will work primarily with Python libraries like pandas, numpy, scikit-learn, and PyTorch, alongside SQL, Apache Spark, AWS services, and Git for version control.
What projects will this role handle?
The position involves building machine learning and deep learning models for fraud detection, credit risk analysis, recommendation systems, churn prediction, and purchase propensity.
The application is on the official Inter Carreiras careers page.
Apply on company site