Data Scientist Mid/Senior – Consulting

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Datarisk

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

💼 Consulting

🏥 Healthcare

📣 Marketing

Consulting • Healthcare • Marketing

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 deep exploratory data analysis (EDA) and generate actionable insights • Build and validate statistical and Machine Learning models • Perform feature engineering, model evaluation and improvement • Integrate solutions with data engineering and technology • Create and implement monitoring for models in production • Document and communicate results to technical and business stakeholders • For the senior position: make autonomous technical decisions • For the senior position: lead complex, high-impact end-to-end projects • For the senior position: mentor and review the work of mid-level and junior professionals • For the senior position: communicate with and influence senior stakeholders (Management/Directors)

🎯 Requirements

• Degree in Mathematics, Statistics, Data Science or Engineering • Master’s/PhD in related fields is desirable • Strong knowledge of Python (pandas, NumPy, scikit-learn) • Solid understanding of predictive modeling, statistics and evaluation metrics • Advanced SQL for data analysis and transformation • Experience with deploying and monitoring models in production • Strong skills in code review, coding standards, testing and best practices • Ability to adapt language and communicate technical results to non-technical clients • Preferred: experience with credit, collections and fraud models • Preferred: experience in consulting or across multiple business domains • Preferred: experience with distributed pipelines (Spark/Databricks) • Preferred: proficiency in cloud platforms (AWS, Azure or GCP) • Preferred: experience with MLOps (MLflow, Kubeflow, SageMaker, etc.) • Preferred: NLP, generative AI or unstructured data analysis • Preferred: experience with mentoring and technical leadership, especially for senior roles

🏖️ Benefits

• Flexibility: remote-first team with the ability to work from anywhere • Health and dental plan (Bradesco) • Wellhub (formerly Gympass) • Conexa Saúde & Psicologia Viva • 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 • Contracting model: PJ (contractor)