Senior Data Scientist

CI&T

Senior Data Scientist at CI&T developing analytical solutions to ensure data integrity for critical business decisions. Collaborating with various teams to enhance data quality and governance.

Posted 7/22/2026full-time🇧🇷 BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building statistical and predictive models, utilizing Python and SQL for data analysis, and applying data quality practices. Proficient in working with large datasets and implementing data governance initiatives within financial institutions.

Highest-signal resume keywords

Statistical ModelingPredictive ModelingData Quality PracticesGraph ModelingCloud Environments

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Statistical ModelsPredictive ModelsLinear RegressionLogistic RegressionDecision TreesRandom ForestGradient BoostingClassification ModelsClustering ModelsData Profiling

Soft Skills

CollaborationDocumentation

Tools & Technologies

PythonSQLAzureDatabricksNeo4jGraph Data ScienceAzure MLGenerative AILLMsMultimodal Models

Industry Keywords

Master Data ManagementData GovernanceFinancial InstitutionsBanksInsurance Companies

Tech Stack

Tools & technologies

AzureCloudNeo4jPythonSQL

About the role

Key responsibilities & impact

Conduct studies and analyses to identify gaps, inconsistencies, and opportunities for improvement in customer/master data.
Build statistical and predictive models for inference, recommendation, and data enrichment.
Develop Golden Record models to ensure the best version of the customer record.
Use graph techniques to identify complex relationships and opportunities in the master data, such as link detection, clustering, and relationship patterns between entities.
Work with large volumes of structured and unstructured data.
Apply data profiling, imputation, and enrichment techniques.
Collaborate with business and engineering teams to continuously improve data quality.
Support governance initiatives and MDM (Master Data Management) projects.
Document methodologies, processes, and results clearly and accessibly.

Requirements

What you’ll need

Proven experience building statistical and predictive models (Linear and Logistic Regression, Decision Trees, Random Forest, Gradient Boosting).
Proficiency in Python and SQL.
Experience with classification and clustering models (K-Means, DBSCAN, etc.).
Knowledge of graph modeling and analysis (e.g., Neo4j, Graph Data Science) is a strong advantage.
Experience with cloud environments (preferably Azure and Databricks).
Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, Economics, or related fields.
Experience in financial institutions, banks, and/or insurance companies.
Knowledge of data modeling and data quality practices.
Familiarity with Azure ML, Databricks, and other AI platforms.
Experience with GenAI and modern data science techniques (LLMs, embeddings, multimodal models).
Participation in corporate master data, CRM, or data governance projects.
Desirable knowledge of Generative AI (GenAI) and modern data analysis techniques.
Experience in projects that use graphs for relationship analysis and insight discovery.

Benefits

Comp & perks

Health and dental insurance;
Meal and food allowance;
Childcare assistance;
Extended parental leave;
Partnerships with gyms and health & wellness professionals via Wellhub (Gympass) TotalPass;
Profit Sharing (PLR);
Life insurance;
Continuous learning platform (CI&T University);
Discount club;
Free online platform dedicated to promoting physical and mental health and well-being;
Pregnancy and parenting course;
Partnerships with online course platforms;
Language learning platform;
And many more