Product Specialist – Data Science

PagBank

Data Science Specialist at PagBank developing and analyzing financial models and insights. Collaborating with cross-functional teams to enhance business performance in financial transactions and products.

Posted 6/2/2026full-timeSao Paulo • 🇧🇷 BrazilMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Develop statistical, predictive and analytical models to project TPV (Total Payment Volume), revenues, costs and the main financial lines of the acquiring business.
Analyze large volumes of transactional, financial and behavioral data to identify patterns, trends, risks and opportunities to improve business results.
Build and evolve forecast models to support financial planning, performance monitoring and strategic decision-making for acquiring, acquisition and macro-products.
Analyze variances between actuals, budget and forecast, explaining performance deviations and their main drivers, such as seasonality, customer behavior, product mix, acquisition channels and market dynamics.
Develop segmentations of customers, products and channels to support growth, profitability, efficiency and commercial prioritization strategies.
Work closely with product, finance, pricing, planning, data engineering and business teams to define assumptions, structure analyses and implement data-driven solutions.
Translate complex business problems into analytical models, metrics, KPIs and actionable recommendations for stakeholders at different levels.
Deliver complex insights clearly, executive-style and effectively to technical and non-technical stakeholders, supporting strategic decisions related to growth, profitability and financial efficiency.
Build analytical views, dashboards and recurring studies to track TPV, revenue, costs, margin, profitability, customer acquisition and macro-product performance.
Mentor and provide technical guidance to junior data team members, contributing to the analytical development of the area.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, Business Administration, Actuarial Science or related fields.
Experience analyzing large volumes of transactional and financial data to generate actionable insights for business teams.
Experience developing forecast models, financial projections, time series analysis, statistical modeling or predictive models.
Knowledge of merchant acquiring metrics, payment methods, banking, financial products or transactional businesses.
Experience with data analysis tools and programming languages such as SQL, Python or R, and machine learning/statistics libraries like Scikit-Learn, Statsmodels, Prophet, TensorFlow or PyTorch.
Ability to structure variance analyses between actuals, budget and forecast, identify root causes and clearly explain financial impacts.
Ability to solve complex problems in a creative, structured and data-driven manner.
Familiarity with code versioning processes such as Git and GitHub.
Ability to translate business teams' questions and needs into analytical requirements, models, metrics and practical recommendations.

Benefits

Comp & perks

Meal allowance and/or meal voucher.
Health and dental insurance.
Life insurance.
Partnerships with TotalPass and ZenKlub.
Extended maternity and paternity leave.
Childcare assistance.
Up to 50% discounts on postgraduate and MBA programs from leading institutions such as FIA, FAAP and PUCRS.
No dress code: wear what makes you comfortable.
#TáDeParabéns: day off on your birthday.
Baby gift: present for newborns.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

statistical modelingpredictive modelsforecast modelstime series analysisdata analysisvariance analysismachine learningSQLPythonR

Soft Skills

problem-solvinganalytical thinkingcommunicationmentoringcollaborationcreativitystructured thinkingdata-driven decision makingtranslating business needsexecutive communication