Mid/Senior Data Scientist – Consulting

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🕒 January 15

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Datarisk

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

🤖 Artificial Intelligence

☁️ SaaS

💳 Fintech

Artificial Intelligence • SaaS • Fintech

Datarisk is a data science and AI company that provides an MLOps platform, Model-as-a-Service (MaaS), credit-scoring solutions and AI agents to help organizations train, deploy and monitor machine learning models. It focuses on improving decision-making and risk management for financial institutions, fintechs and enterprises across sectors (marketing, supply chain, people analytics, retail and healthcare) by delivering cloud-hosted predictive models, specialized credit scores and consulting services. Datarisk positions itself as a B2B SaaS provider of machine learning and AI-driven products and services.

📋 Description

• Understand business problems and define analytical hypotheses; • Perform in-depth exploratory data analysis (EDA) and generate actionable insights; • Build and validate statistical and machine learning models; • Perform feature engineering, evaluate and improve models; • Integrate solutions with data engineering and technology teams; • Implement and maintain monitoring for models in production; • Document and communicate results to technical and business stakeholders; • Additional responsibilities for Senior: Make independent technical decisions. Lead complex, high-impact end-to-end projects. Mentor and review the work of mid-level and junior colleagues. Communicate with and influence senior management/executive stakeholders.

🎯 Requirements

• Degree in Mathematics, Statistics, Data Science, or Engineering; master’s or PhD in related fields is desirable; • Strong knowledge of Python (pandas, numpy, scikit-learn); • Strong background in predictive modeling, statistics, and evaluation metrics; • Advanced SQL for data analysis and transformation; • Experience deploying and monitoring models in production; • Strong skills in code review, coding standards, testing, and best practices; • Ability to adapt communication and present technical results to non-technical clients; • Experience with credit, collections, and fraud models is a plus; • Experience in consulting or across multiple business domains; • Experience with distributed pipelines (Spark/Databricks); • Proficiency in Cloud platforms (AWS, Azure, or GCP); • Hands-on experience with MLOps tools: MLflow, Kubeflow, SageMaker, etc.; • Experience with NLP/generative AI or unstructured data analysis; • Experience mentoring and providing technical leadership (especially for senior candidates).

🏖️ Benefits

• Flexibility — our team is remote, you can work from anywhere; • Bradesco health and dental insurance; • Wellhub (formerly Gympass); • Conexa Saúde & Psicologia Viva (health and mental health services); • Corporate partnership with Open English (discounts on English & Spanish courses); • Caju: home office allowance; • Paid leave of 22 business days per year; • Birthday day off; • Contractor (PJ) employment model.