Location
Hybrid (São Paulo, Brazil)
Seniority
Senior · 6+ years exp
Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Sep 8, 2026. Kstack scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Kstack is a Brazilian technology boutique that supplies IT consulting, software engineering and recruiting to clients. Its teams cover tech leadership, site reliability, SAP development and technical recruiting, working with clients in Sao Paulo, Cuiaba and Barueri. The company is headquartered in Sao Paulo, Brazil.
Location: São Paulo, Brazil
About the Role
We are looking for an experienced Data Scientist with 6+ years of overall professional experience, including at least 3+ years of hands-on experience in Data Science, Machine Learning, and advanced analytics.
The ideal candidate has strong expertise in developing and deploying machine learning models, analyzing complex datasets, and translating business challenges into data-driven solutions. This role requires close collaboration with engineering, product, and business teams to design and deliver scalable AI/ML solutions that drive measurable business outcomes.
Key Responsibilities
- Design, develop, train, validate, and deploy machine learning and statistical models to solve complex business problems.
- Analyze large and complex datasets to identify trends, patterns, correlations, and actionable insights.
- Translate business requirements and challenges into effective Data Science and Machine Learning solutions.
- Perform data preprocessing, feature engineering, Exploratory Data Analysis (EDA), and model evaluation.
- Develop predictive models using classification, regression, clustering, and other Machine Learning techniques, as appropriate.
- Optimize and fine-tune models to improve accuracy, scalability, and performance.
- Collaborate closely with Data Engineers, Software Engineers, Product Managers, and business stakeholders.
- Design and implement end-to-end Data Science solutions, from data preparation through model deployment.
- Monitor model performance in production and continuously improve models based on evolving business and production requirements.
- Communicate complex analytical findings and model results clearly and effectively to both technical and non-technical stakeholders.
- Follow engineering and Data Science best practices for code quality, documentation, testing, version control, and model governance.
Required Skills & Qualifications
- 6+ years of overall professional experience in software, analytics, data, or related technical roles.
- 3+ years of hands-on experience specifically as a Data Scientist.
- Strong programming skills in Python.
- Strong understanding of Machine Learning algorithms, techniques, and core concepts.
- Hands-on experience with libraries and frameworks such as scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
- Strong foundation in statistics, probability, data modeling, and experimental design.
- Hands-on experience with data preprocessing, feature engineering, model training, validation, and evaluation.
- Strong SQL skills and experience working with relational databases and/or large-scale data platforms.
- Experience with data visualization tools such as Power BI, Tableau, Matplotlib, or similar technologies.
- Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Understanding of MLOps, model deployment, CI/CD, and production Machine Learning workflows is highly preferred.
- Experience working with large datasets and distributed data processing frameworks such as Apache Spark/PySpark is a plus.
- Strong analytical, problem-solving, and communication skills.
Preferred / Nice-to-Have Qualifications
- Experience with Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), or Retrieval-Augmented Generation (RAG).
- Experience with frameworks such as LangChain, LlamaIndex, or similar technologies.
- Knowledge of Deep Learning and NLP techniques.
- Experience with Docker, Kubernetes, Git, and CI/CD pipelines.
- Experience building and deploying Machine Learning models using cloud-native services.
- Experience working in Agile/Scrum environments.
Education
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
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