Mid-level Data Scientist

NEORIS is a Digital accelerator that helps companies enter the future, having 20 years of experience as Digital Partners of some of the largest companies in the world. We have more than 4,000 professionals in 11 countries, with our multicultural startup culture where we cultivate innovation, continuous learning to create high-value solutions for our clients.

We are looking for a motivated Mid level Data Scientist with experience in Python, statistical analysis, and machine learning to support the development of data-driven and AI-powered solutions. In this role, you will collaborate with senior data scientists, engineers, and business stakeholders to analyze data, build predictive models, and contribute to scalable analytics and AI applications.

• →Model Development: Support the implementation of machine learning models, assisting with data preprocessing, feature engineering, model training, and evaluation.
• →Statistical Analysis: Apply techniques such as regression, classification, clustering, and anomaly detection to solve business and operational problems.
• →AI Innovation: Assist in developing applications using Generative AI (LLMs, prompt engineering, embeddings, or Retrieval-Augmented Generation).
• →Integration: Work with APIs and backend services to integrate ML and AI models into internal systems.
• →Workflow Optimization: Support the development of scalable ML workflows and data pipelines for experimentation and training.
• →Cross-functional Collaboration: Partner with data engineers, DevOps and software developers to support the deployment and monitoring of models.
• →Code Quality: Write clean, well-documented code using Python and SQL.
• →Data Storytelling: Prepare visualizations and reports to communicate insights and results to both technical and non-technical stakeholders.

• Professional Experience: 2+ years working with Python in data science, analytics, or machine learning projects.
• Database Skills: Practical experience with SQL for querying and analyzing large datasets.
• ML Frameworks: Experience supporting ML models using libraries such as scikit-learn, PyTorch, or TensorFlow.
• Data Processing: Familiarity with data processing or streaming pipelines (e.g. Apache Beam, Google Cloud Dataflow, Spark, or similar frameworks).
• Technical Literacy: Familiarity with REST APIs, web services, Generative AI concepts and frameworks (LLMs, RAG-based systems, LangChain, ADK, Llama-index).
• Soft Skills: Strong analytical thinking, problem-solving skills, and English proficiency (B2 level or higher).

• Version Control: Experience with Git and version control practices.
• Cloud & DevOps: Exposure to cloud environments (GCP, AWS, or Azure) and MLOps concepts (CI/CD, Docker, Kubernetes, or MLflow).
• Agile Mindset: Experience working in Agile development environments.
• Portfolio: Personal projects, research, or AI experimentation that demonstrate initiative and curiosity.

• Curiosity: A strong desire for continuous learning and exploring new tools in AI/ML.
• Initiative: A self-driven approach to developing skills and solving technical hurdles.
• Persistence: The ability to iterate through complex challenges toward effective solutions.
• Ownership: Accountability for technical tasks and a collaborative, supportive mindset.