Data Scientist

At Xpand IT, the Data Science team is dedicated to transforming data into high-impact solutions using advanced modeling and industry-leading algorithms. We work on complex challenges ranging from optimization and forecasting to recommendation systems, ensuring our solutions are scalable, robust, and deployed in real-world contexts. Our work goes beyond model creation: it involves building pipelines, integrating with existing systems, and collaborating closely with both engineering and business teams.

Your role:

As a Data Scientist, you will participate in E2E projects, from raw data collection and processing to deploying models into production. You will also have a strong research component, being responsible for exploring the market and new technologies. Your focus will be:

• Developing and training predictive models, recommendation systems, and Machine Learning algorithms;
• Leading R\&D initiatives by conducting research and developing PoCs to test new technologies and approaches (e.g., GenAI and LLMs);
• Building and maintaining data and machine learning pipelines (batch and near real-time) and evaluating trade-offs between performance, cost, and complexity;
• Managing the full project lifecycle: extraction, preparation, manipulation, and model optimization;
• Collaborating with engineering and business teams to translate real-world problems into data-driven solutions.

Tech stack:

• Core language: Python (Pandas, NumPy, Scikit-learn);
• Deep learning: TensorFlow, Keras, PyTorch;
• Data \& ML: PySpark, MLflow, Airflow, Azure ML;
• GenAI: LLMs, Llama;
• Cloud: Azure, Google Cloud, or AWS;
• Exploration: SQL and data visualization tools.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Data Science, or related fields.
• Solid experience (minimum 1 year) in developing and training Machine Learning models and Data Mining algorithms.
• Strong expertise in the Python ecosystem for data and mathematics (NumPy, SciPy, Pandas, Scikit-learn).
• Hands-on experience in all phases of a data project, including raw data preparation and database manipulation (SQL).
• Ability to conduct technical research, create proofs of concept (PoCs), and evaluate new tools or frameworks.
• Mandatory fluency in both Portuguese and English (written and spoken).

Nice to have:

• Practical experience with GenAI, LLMs, and Prompt Engineering techniques;
• Strong statistical background (regressions, distributions, and normality testing);
• Experience with AI services in public Cloud environments (Azure, Google Cloud, or AWS);
• Passion for sharing technical knowledge and keeping up with market trends.