
1001 - 5000 employees
Founded 1996
đ€ B2B
đŒ Consulting
B2B âą Data Analytics âą Consulting
Keyrus is an international company passionate about leveraging data to make impactful changes in life, society, and the future. With a presence in 18 countries, Keyrus is dedicated to creating meaningful careers for its employees by fostering excellence, trust, creativity, kindness, and fun. Specializing in data analytics, data advisory, and management, Keyrus provides vendor-agnostic solutions and continuous training opportunities through its KLX platform. The company also emphasizes a healthy work-life balance with a range of benefits, including sports events, healthcare plans, and an inclusive work culture. Keyrus is committed to openness and transparency to maintain positive workplace relationships and is driven to innovate and influence the digital future.
đ August 14
đ§đ· Brazil â Remote
â° Full Time
đĄ Mid-level
đ Senior
đ Data Scientist
đ» Ghost score 27%
đŁïžđ§đ·đ”đč Portuguese Required
Where this job comes from
Posted on Keyrus's careers page â, not through a job board
First seen by Remote Rocketship August 14
Still open on Keyrus's site. Checked 3 hours ago.

1001 - 5000 employees
Founded 1996
đ€ B2B
đŒ Consulting
B2B âą Data Analytics âą Consulting
Keyrus is an international company passionate about leveraging data to make impactful changes in life, society, and the future. With a presence in 18 countries, Keyrus is dedicated to creating meaningful careers for its employees by fostering excellence, trust, creativity, kindness, and fun. Specializing in data analytics, data advisory, and management, Keyrus provides vendor-agnostic solutions and continuous training opportunities through its KLX platform. The company also emphasizes a healthy work-life balance with a range of benefits, including sports events, healthcare plans, and an inclusive work culture. Keyrus is committed to openness and transparency to maintain positive workplace relationships and is driven to innovate and influence the digital future.
âą Transform complex business challenges into scalable, modern, and outcome-driven data solutions âą Develop and evaluate statistical and machine learning models âą Build generative AI solutions using RAG, embeddings, vector search, and prompt engineering âą Prepare data, perform feature engineering, train models, validate results, analyze errors, and measure performance âą Take analytical or AI solutions from prototype to production âą Ensure quality, monitoring, security, performance, cost control, and governance throughout the model lifecycle âą Collaborate with Product Managers, Architects, Engineers, Data Governance teams, and business specialists âą Influence decision-making and build trusted relationships with stakeholders âą Contribute to AI assistants, forecasting solutions, recommendation systems, or decision-support products âą Work with agentic workflows, function calling, and multi-step AI applications
âą Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field âą Over 5 years of professional experience developing and deploying data science, machine learning, or AI solutions âą Strong proficiency in Python, including pandas, NumPy, scikit-learn, and relevant deep learning or generative AI frameworks âą Hands-on experience in data preparation, feature engineering, model training, validation, error analysis, and performance measurement âą Experience taking analytical or AI solutions from prototype to production âą Practical knowledge of Git, testing, code review, documentation, APIs, and CI/CD practices âą Experience with cloud data and AI platforms, preferably SageMaker, Databricks, or equivalent technologies âą Familiarity with MLOps practices, including experiment tracking, model versioning, deployment automation, and monitoring âą Practical understanding of LLMs, embeddings, vector databases, RAG, and GenAI solution evaluation âą Excellent communication skills with technical and non-technical audiences âą Ability to translate business needs into practical, scalable solutions âą Analytical mindset, autonomy, critical thinking, and a strong desire for continuous learning
âą Culture of equality âą Diversity and multiculturalism âą Collaboration across specialties, functions, and geographies âą Knowledge sharing and continuous improvement âą Opportunities to work with people from different parts of the world
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