Senior Data Scientist

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Addvisor Group

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2004

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Addvisor Group is a Brazilian enterprise software and consulting company that provides fiscal and business-process automation solutions for medium and large companies. Its flagship product, AddTax (and SmartDocx), is a SaaS platform that automates capture, orchestration and compliance of fiscal documents (NF-e, NFS-e, CT-e, MDF-e, etc. ), integrates natively with SAP (ECC and S/4HANA) and via APIs with other ERPs, and supports tax compliance across thousands of Brazilian municipalities and multiple countries. Addvisor also offers implementation and consulting services, including ERP selection and SAP implementations, focused on reducing operational costs, fines and improving financial and tax efficiency.

📋 Description

• Develop and apply business-focused Data Science projects • Work on forecasting and service-level targets • Build and maintain large-scale data pipelines • Optimize code performance and develop allocation/optimization algorithms • Develop multi-echelon inventory simulations • Create solutions with Streamlit/Plotly and support infrastructure, Terraform, and CI/CD • Technically lead projects or mentor other data scientists

🎯 Requirements

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or related fields • Solid experience in Data Science with business-applied projects • Advanced Python skills, including NumPy and Pandas; Polars is a plus • Knowledge of statistics/probability applied to forecasting and service-level • Experience with PySpark and large-scale data pipelines • Experience with AWS, including Glue and S3 • Experience with performance optimization in Python, including Numba JIT, and allocation/optimization algorithms • Experience with multi-echelon inventory simulation • Knowledge of Streamlit/Plotly, Terraform, and CI/CD • Experience with AWS Step Functions • Experience technically leading projects or mentoring other data scientists