DATA SCIENTIST III | DATA ENGINEERING & SCIENCE

About the Position

DATA SCIENTIST III | DATA ENGINEERING & SCIENCE

Belo Horizonte, MG; Curitiba, PR; Recife, PE; São Paulo, SP

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Conheça o Inter

Pioneiros, mudamos o mercado ao lançar o primeiro banco digital do Brasil e seguimos criando tendências com tecnologia de ponta. Evoluímos para um Super App Financeiro Global, com soluções completas e inovação de primeira. Aqui, o trabalho tem propósito: construir oportunidades reais, transformar a vida das pessoas e o mercado financeiro. Esse é o nosso Jeito Inter de Fazer. Se você quer fazer parte dessa mudança e deixar um legado, seu lugar é aqui.

Vem ser Sangue Laranja.

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Get to Know Inter

As pioneers, we transformed the market by launching Brazil’s first digital bank and continue to shape the future with cutting-edge technology.

We have evolved into a Global Financial Super App, delivering complete solutions and leading innovation. Here, work has purpose: creating real opportunities, transforming people’s lives, and reshaping the financial market.

This is the Inter way of making things happen. If you want to be part of this transformation and leave your mark, your place is here.

Become Sangue Laranja.

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About the Role and Mission

You will be part of our Data Science team as a senior technical reference and will directly work on building intelligent solutions that impact millions of Inter customers. Your mission will be to transform large volumes of data into predictive models and strategic insights, technically leading end-to-end initiatives and being a key player in the evolution of our financial and digital product ecosystem.

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Daily Responsibilities

• Conduct exploratory analyses of large volumes of transactional and behavioral data to identify actionable insights and business opportunities.
• Build and implement machine learning and deep learning models applied to real-world problems such as fraud detection, credit risk analysis, recommendation systems, churn prediction, and purchase propensity.
• Validate hypotheses through controlled experiments with A/B testing methodologies and statistical analysis.
• Technically lead end-to-end data science projects, from conception to production delivery.
• Act as a technical reference within the team, supporting the development of junior and full data scientists through code reviews and technical guidance.
• Collaborate with product owners and engineers to translate business challenges into robust and scalable analytical solutions.
• Contribute to the definition of best practices, technical standards, and the evolution of the data culture within the organization.

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Requirements

Required:

• Solid experience with machine learning models in production and large-scale environments, with a proven track record of delivering business value.
• Proficiency in Python with libraries such as pandas, numpy, matplotlib, scikit-learn, PyTorch.
• Advanced experience in SQL for data manipulation and querying large volumes of data.
• Experience with Apache Spark for distributed processing of large datasets.
• Knowledge of AWS services (such as S3, SageMaker, Glue, EMR, or similar) for data solution development and deployment.
• Mastery of Git for code versioning and collaboration in technology teams.
• Solid foundation in descriptive and inferential statistics, hypothesis testing, and probability concepts.
• Ability to explore complex datasets, identify patterns, and work with structured and semi-structured data.
• Technical communication skills to present results and insights clearly to diverse audiences (data storytelling).
• Experience with the complete model development cycle, including monitoring, retraining, and maintenance in production (MLOps).

Desirable:

• Experience in developing machine learning solutions in a production environment.
• Experience with Apache Airflow for data pipeline orchestration and scheduling.
• Experience with A/B testing methodologies in a digital product environment.
• Experience in technology or fintech companies with high data volumes.
• Experience in technical leadership or mentoring data teams.
• Knowledge of feature store tools, model monitoring (such as MLflow or similar), and advanced MLOps practices.
• Intermediate or advanced English for reading technical documentation and communicating with global teams.

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Benefits

• Meal and food vouchers
• Health and dental insurance
• Life insurance
• Birthday DayOff
• Baby On Board and Breastfeeding Room
• Extended parental leave
• Childcare/nanny assistance and/or assistance for children with disabilities
• Wellhub and Inter Running Group
• CARE4U Space (Belo Horizonte): self-care services with exclusive values, decompression area, games, and mini golf course
• Advantages in our SuperApp, such as Duo Gourmet
• Prime Inter Card
• Internal training and development programs

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Selection Process Stages

• Resume screening;
• Initial screening (initial approach to align expectations about the position);
• Assessments;
• Interview with the Talent Team;
• Technical test (when necessary);
• Interview with leadership;
• Job offer;

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