Where this role is available
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- Brazil, Brazil
- Brazil
Role summary by JobGrid
[Job-29597] Senior Data Scientist , Brazil at ciandt: Brazil, Brazil, Brazil; On-site; IT; Data Science & ML. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Brazil, Brazil, Brazil, On-site
- Role classification: IT, Data Science & ML
- Source freshness: checked by JobGrid on 2026-06-10.
- Application path: candidates continue to the employer application page with non-personal referral tags.
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
We are looking for a Senior Data Scientist to join a global retail and consumer goods company. This professional will be responsible for leading Machine Learning and Analytics initiatives, from identifying business opportunities to deploying and supporting production-ready solutions.
Key Responsibilities
Discovery & Solution Definition
- Understand business challenges and translate them into analytical and technical hypotheses.
- Partner with Product Owners and stakeholders to define data and AI products.
- Evaluate the most suitable solution consumption model (real-time, batch, dashboards, APIs, or insights).
- Support the definition of business rules and requirements for Machine Learning products.
Development & Deployment
- Perform exploratory data analysis (EDA) and validate hypotheses.
- Design and develop Machine Learning models and experimentation pipelines.
- Define data architecture, algorithms, and product evolution roadmaps.
- Implement, test, optimize, and review model and pipeline code.
- Establish deployment, orchestration, and monitoring processes for production models.
- Support solution maintenance and continuous product improvement.
Communication & Results Management
- Present results and recommendations to business stakeholders and leadership teams.
- Define success metrics, benchmarks, and performance indicators.
- Gather and incorporate stakeholder feedback to continuously improve solutions.
Technical Leadership
- Lead technical discussions and prioritize initiatives.
- Mentor data scientists and support the team's technical development.
- Promote best practices in development, governance, and documentation.
Business Partnership
- Translate technical outcomes into measurable business impact.
- Collaborate closely with Product, Engineering, Operations, and Commercial teams.
- Stay current with market trends, innovation, and emerging technologies applicable to the business.
Requirements
Must-Have Qualifications
- Strong experience in Data Science, Machine Learning, or related fields.
- Strong proficiency in Python or R and Machine Learning libraries/frameworks.
- Solid knowledge of statistical modeling, experimentation, and data analysis.
- Experience developing and deploying Machine Learning models into production environments.
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
- MLOps concepts and model monitoring, version control, and pipeline orchestration.
- Strong SQL skills and experience working with large-scale datasets.
- Excellent communication skills, with the ability to interact effectively with both technical and business stakeholders.
- Analytical mindset, consultative approach, and results-oriented attitude.
Nice-to-Have Qualifications
- Experience with Databricks, MLflow, Lakehouse architectures, or similar platforms.
- Knowledge of Generative AI, Large Language Models (LLMs), and RAG architectures.
- Experience in retail, consumer goods, or other large-scale data-driven environments.
- Previous experience providing technical leadership and mentoring team members.