Consultant – Data Science and Advanced Analytics | Financial Services

Description

Job Summary: Accenture is seeking a Data Science Consultant to work on strategic projects in the Financial Services sector, focusing on statistical modeling, AI, and analytics. Key Highlights: 1. Lead technical fronts for modeling and analytics in high-impact projects 2. Bridge quantitative rigor with business vision to deliver measurable outcomes 3. Develop robust solutions and communicate results to executive audiences **About Accenture** Accenture helps the world’s leading companies reinvent themselves by building their digital core and unlocking the power of AI to rapidly generate value across organizations in all industries. Our strategy is to be our clients’ preferred reinvention partner, lead the secure and scalable adoption of AI, be the most customer-centric AI-powered company, and be the best place to work. We bring together the talent of approximately 786,000 people with proprietary assets and platforms, deep process and industry expertise, and leading relationships across the ecosystem to deliver integrated solutions and measurable, scaled outcomes. Through our Reinvention Services, we offer broad expertise in Cybersecurity, Digital Core, Finance, Industry & Enterprise, Song, Supply Chain & Engineering, and Talent—with advanced capabilities in AI and Data, Industry & Processes, and Technology. We serve approximately 9,000 clients and generated approximately $70 billion in revenue in fiscal year 2025. Visit Accenture at accenture.com. **The Opportunity:** Accenture is seeking a Consultant to work on strategic projects in the Financial Services sector, with a focus on data science, statistical modeling, advanced segmentation, analytics, and artificial intelligence. In this role, you will lead technical fronts for modeling and analytics in high-impact projects, connecting quantitative rigor with business vision to deliver measurable outcomes for clients across the financial ecosystem. We seek a candidate with proven experience in data science applied to the financial sector, capable of developing robust solutions, communicating results to executive audiences, and contributing to high-quality consulting project delivery.**What You’ll Do Daily:** * Lead the 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 (K-Means, DBSCAN, Gaussian mixture models, behavioral segmentation) to support activation, pricing, and portfolio management strategies. * Develop machine learning models for critical applications such as 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 techniques—to support business decisions. * Translate technical findings into clear business recommendations, structuring analytical narratives and executive presentations that link modeling to financial impact. * Coordinate analytical workstreams, guide analysts, and ensure technical quality of deliverables, methodologies, and documentation. * Support the development of data strategies, model governance, monitoring frameworks, and MLOps best practices in financial services environments. * Contribute to commercial proposals, RFPs, thought leadership assets, and Accenture’s Data & AI practice methodologies. **What We’re Looking for in the Person Joining Our Team:** * Experience in data science applied to the financial sector—either in consulting or technical roles within banks, fintechs, finance companies, or credit bureaus. * Advanced proficiency in Python and/or R for statistical modeling, machine learning, and data analysis, with strong command of libraries such as scikit-learn, XGBoost, LightGBM, statsmodels, scipy, and pandas. * Solid knowledge of supervised and unsupervised machine learning techniques, classical statistical modeling, and advanced segmentation and clustering methods. * Experience across the full modeling lifecycle: problem definition, data collection and preparation, feature engineering, training, validation, interpretation, and model monitoring. * Ability to communicate technical results to non-technical audiences, building decision-oriented analytical narratives and high-quality executive materials. * Fluency in SQL and experience with big data and cloud platforms (Databricks, Spark, AWS, Azure, or GCP). * Advanced English for meetings, technical documentation, and global collaboration. * Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Physics, Quantitative Economics, or related fields. **Additionally, desirable knowledge includes:** * Experience in credit scoring modeling, PD/LGD/EAD, fraud detection, delinquent portfolio segmentation, payment propensity, or churn in financial services. * Experience with MLOps, model versioning, production deployment, and performance and drift monitoring. **Benefits:** Health Insurance – 100% company-subsidized (for employee and dependents) Dental Insurance ️ Meal or Food Allowance – no payroll deduction ️ Life Insurance Private Pension Plan ️ Welhub* Option to purchase company stock at a discount Pharmacy Discount* Childcare Assistance* Language School Partnership* ‍‍ Extended Maternity and Paternity Leave PPR* * As per current policy **Location:** Hybrid – São Paulo/SP