Product Specialist – Data Science

Role Overview

• 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

• 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.

Tech Stack

• Python
• PyTorch
• Scikit-Learn
• SQL
• Tensorflow

Benefits

• 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.