Senior Data Scientist

AM53 Smart Solutions

. Develop models to optimize banking or acquiring processes.

Posted 10/3/2026full-timeSão Paulo • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data analysis and modeling to optimize banking processes, utilizing programming languages and machine learning libraries. Capable of translating complex data insights into actionable strategies for business teams while mentoring junior data science members.

Highest-signal resume keywords

Data AnalysisSQLPythonMachine LearningMentoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingStatistical AnalysisBehavioral Prediction AlgorithmsCustomer SegmentationProblem Solving

Soft Skills

Creative ThinkingCommunication

Tools & Technologies

TensorFlowPyTorchScikit-LearnGitGitHub

Industry Keywords

BankingAcquiring ProcessesTransactional DataData SolutionsStakeholder Engagement

Tech Stack

Tools & technologies

PythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Develop models to optimize banking or acquiring processes.
Analyze large volumes of transactional data to identify patterns, trends, and opportunities to improve processes.
Implement customer segmentation and behavioral prediction algorithms to increase the efficiency and personalization of the services offered.
Work closely with engineering, product, and business teams to define and implement data solutions that meet the needs of customers and the company.
Present complex insights clearly and effectively to non-technical stakeholders, supporting strategic decision-making.
Mentor and provide technical guidance to less senior members of the data science team.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
Experience analyzing large volumes of data to generate insights for business teams.
Experience with data analysis and programming tools such as SQL, Python, R, or machine learning libraries (TensorFlow, PyTorch, Scikit-Learn, etc.).
Ability to solve complex problems creatively and innovatively.
Knowledge of code version control processes and tools (Git, GitHub).
Ability to translate business teams’ questions and needs into requirements for analysis.