Data Scientist – Focus on Credit and Business Solutions

Sicredi

Data Scientist focusing on Credit and Business solutions at Sicredi. Responsible for data analysis, deriving insights, and improving credit strategies.

Posted 7/13/2026full-time🇧🇷 BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in statistical and machine learning techniques, data architecture, and advanced data analysis using SQL, R, and Python. Capable of effectively communicating complex analyses and fostering a data-driven culture within teams.

Highest-signal resume keywords

Statistical And Econometric ModelingMachine Learning FrameworksData ArchitectureCloud Platforms (AWS)Advanced Data Visualization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLRPythonMachine LearningStatistical ModelingData ProcessingData GovernanceAdvanced StatisticsModel DeploymentData Storytelling

Soft Skills

Clear CommunicationEmpathyCollaborationCritical ThinkingProblem-Solving

Tools & Technologies

GitGitLabTensorFlowPyTorchScikit-learnPower BIPlotlySeaborn

Industry Keywords

Data ScienceData-Driven CultureMLOpsETL PipelinesLGPD Compliance

Tech Stack

Tools & technologies

AWSETLPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Prepare scenario studies and business diagnostics;
Develop and support teams in measuring results, identifying opportunities, trends and patterns in datasets;
Take initiative to propose hypotheses and solve problems using data science;
Ability to present and communicate analyses in non-technical terms;
Work in partnership with Data Engineers to improve data acquisition and transformation flows used in models;
Collaborate with Data Analysts to generate business insights and steer information analysis for better strategic decisions;
Ensure the quality, performance and sustainability of models;
Participate in the Data Science Chapter, encouraging and promoting a data-driven culture across colleagues and teams;
Maintain necessary documentation for your deliverables;
Continuously evolve technically and in business understanding;
Understand and apply statistical and machine learning techniques to propose changes, provide decision-making support and embed models and intelligent algorithms into software products;
Extract and process data from multiple sources and at large scale.

Requirements

What you’ll need

Bachelor’s degree in Engineering, Economics, Statistics, Mathematics, Computer Science and/or related fields.
Languages for advanced analysis (SQL, R, Python)
Version control and CI/CD tools (Git, GitLab or similar)
ML/AI frameworks (TensorFlow, PyTorch, Scikit-learn)
Advanced statistics applied to data science (inference, hypothesis testing, multivariate analysis)
Statistical and econometric modeling (regressions, time series, survival models)
Experience with production environments (model deployment, MLOps, monitoring)
Experience with cloud platforms (AWS)
Building queries for relational and non-relational databases (advanced SQL, optimization)
Data architecture (modeling, ETL pipelines, integration)
Advanced visualization and data storytelling (Power BI, Plotly, Seaborn)
Data governance and LGPD compliance (Brazilian Data Protection Law)
Clear and concise communication
Empathy and collaboration
Critical and analytical thinking
Problem-solving focus

Benefits

Comp & perks

14th and 15th fixed salary payments
Profit-sharing (based on seniority)
Health and dental plans with no co-pay
Wellbeing programs through Wellhub (formerly Gympass): Nutrition, Psychology, Occupational Health, Massage, running groups and access to a local gym
Meal and food allowances (VA/VR) – flexible percentage allocation between cards, no co-pay
Extended maternity and paternity leave
Childcare or nanny allowance for children up to 6 years and 11 months
Assistance for children with disabilities, no age limit
Life insurance
Private pension plan up to 7% of salary
Training platform – Sicredi Aprende, offering a variety of courses
40-hour workweek – using a time bank system
Remote work allowance (except for positions that are 100% on-site)