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Senior Data Scientist
Location
Brazil
Posted
2 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Scientist
Marathon Talent
Role Description As a Senior Data Scientist at R2, you will sit at the helm of R2 by analyzing large data from some of the leading technology platforms in the world, and deploying clever and scalable data-driven solutions that enable new financial opportunities to millions of small businesses across Latin America. Your solutions will drive critical business decisions in an automated and scalable way. - Lead forecasting initiatives by designing and implementing advanced time series models to predict sales and behavioural trends for thousands of customers. - Develop scalable machine learning solutions that power real-time decision-making across risk management, fraud detection, and product personalization. - Collaborate cross-functionally with product managers, engineers, and business stakeholders to translate complex data challenges into actionable insights and measurable business outcomes. - Drive innovation in fintech applications by experimenting with cutting-edge approaches (e.g., deep learning architectures, probabilistic forecasting, and transformer-based models). - Ensure compliance and transparency in model development, aligning with industry regulations and ethical standards for financial data usage. - Shape the data science strategy by identifying opportunities where predictive modeling can unlock new value streams and competitive advantages. Qualifications - At least 5 years of experience with machine and deep learning in a practical setting. - Good understanding of fintech products and risk management to interpret business data effectively. - Strong foundation in probability, statistics, and econometrics. Requirements - Strong expertise in time series forecasting methods based on statistical analysis (ARIMA, SARIMA, SARIMAX, VAR, exponential smoothing, or state-space models). - Expertise in Machine & Deep Learning (Random Forest, XGBoost, RNNs, LSTMs, or Transformers). - Knowledge of Bayesian theory (BSTS, Prophet, or ensemble forecasting). - Deep knowledge of machine learning techniques for sequential data (RNNs, LSTMs, GRUs, Transformers). - Strong proficiency in ML/DL frameworks in Python (e.g. Tensorflow, PyTorch, Scikit-learn). - Comfortable consuming data through APIs, SFTP, or straight-up CSVs. - Experience with explainable AI, especially in the context of Deep Learning Forecasting time series methods. Leadership & Business acumen - Data-oriented mindset: care about making decisions based on data. - Stakeholder management experience, keeping everyone up-to-date with key findings and explaining results, methodologies, and processes for data-driven decision making in a non-technical way.
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