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Accenture

Advises businesses and runs their technology

Consultant Associate - Data Science and Advanced Analytics, Financial Services

Data ScienceConfirmed live in the last 24 hours
Full-timeSão Paulo, State of São Paulo, BrazilNo salary listed

About the Job

Requirements

  • Experience applying data science in the financial sector, either in consulting or technical positions at banks, fintech companies, finance companies, or credit bureaus.
  • Advanced proficiency in Python and/or R for statistical modeling, machine learning, and data analysis, including libraries such as scikit-learn, XGBoost, LightGBM, statsmodels, scipy, and pandas.
  • Strong knowledge of supervised and unsupervised machine learning, classical statistical modeling, and advanced segmentation and clustering techniques.
  • Experience with the complete modeling lifecycle: problem definition, data collection and preparation, feature engineering, training, validation, interpretation, and model monitoring.
  • Ability to communicate technical results to nontechnical audiences, develop decision-oriented analytical narratives, and prepare high-quality executive materials.
  • Fluency in SQL and experience with big data and cloud platforms such as Databricks, Spark, AWS, Azure, or GCP.
  • Advanced English for meetings, technical materials, and interaction in global contexts.
  • A university degree in Statistics, Mathematics, Computer Science, Engineering, Physics, Quantitative Economics, or a related field.

Responsibilities

  • Lead development of predictive, segmentation, and scoring models to support credit, collections, fraud prevention, risk management, and financial product personalization strategies.
  • Design and implement end-to-end data science pipelines, from data exploration and preparation through model validation, deployment, and production monitoring.
  • Apply advanced clustering and customer segmentation techniques, including K-Means, DBSCAN, Gaussian mixture models, and behavioral segmentation, to support outreach, pricing, and portfolio management strategies.
  • Develop machine learning models for applications including probability of default (PD), loss given default (LGD), exposure at default (EAD), payment propensity, anomaly detection, and fraud prevention.
  • Conduct advanced statistical analyses, including hypothesis testing, survival analysis, time series, Bayesian models, and causal inference, to support business decisions.
  • Translate technical results into clear business recommendations and prepare analytical narratives and executive presentations connecting modeling to financial impact.
  • Coordinate analytical workstreams, guide analysts, and ensure the technical quality of deliverables, methodologies, and documentation.
  • Support data strategies, model governance, monitoring frameworks, and MLOps best practices in financial services environments.
  • Contribute to commercial proposals, requests for proposals (RFPs), thought leadership assets, and methodologies for Accenture’s Data & AI practice.

Desired Qualifications

  • Experience with credit scoring, PD/LGD/EAD modeling, fraud detection, delinquent portfolio segmentation, payment propensity, or churn in financial services.
  • Experience with MLOps, model versioning, production deployment, and performance and drift monitoring.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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