Data Scientist

KSTACK; São Paulo; Híbrido; BRL 300 000 - 520 000; Tempo integral

Resumo da oferta

KSTACK in São Paulo, Brazil, is seeking an experienced Data Scientist with 6+ years of professional experience, including 3+ years hands-on in DS/ML and analytics. You will develop and deploy ML models and translate business challenges into data-driven solutions.

You will collaborate with Data Engineers, Software Engineers, Product Managers, and business stakeholders to design end-to-end DS solutions, preprocess data, engineer features, and evaluate models in production.

Qualificações

• 6+ years of overall professional experience in software, analytics, data, or related technical roles.
• 3+ years hands-on as Data Scientist with ML and analytics.
• Strong Python programming and ML algorithm knowledge.
• Experience with scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
• SQL and data modeling experience.

Responsabilidades

• Design, develop, train, validate, and deploy models to solve business problems.
• Analyze large datasets to identify trends and insights.
• Translate business requirements into DS/ML solutions.
• Preprocess data, engineer features, and evaluate models.
• Collaborate with Data Engineers, Software Engineers, Product Managers, and business stakeholders.
• Monitor production models and improve performance.

Conhecimentos

Experience: 6+ yrs

Data Scientist 3+ yrs

Python

ML Algorithms

SQL

ML Frameworks

Statistics

Spark

Communication

Formação académica

Bachelor’s or Master’s in CS/DS/Stats

Ferramentas

scikit-learn

Pandas

NumPy

TensorFlow

PyTorch

Docker

Kubernetes

CI/CD

Git

Cloud: AWS/Azure/GCP

Descrição da oferta de emprego

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.