Role Overview
A Data Scientist with solid experience in Data Science, Machine Learning, and Generative Artificial Intelligence will be responsible for developing and implementing analytical solutions and AI models in production, ensuring scalability and measurable impact for the business.
What You Will Do
Develop, validate, and implement Machine Learning and Generative AI models in production; Translate business needs into analytical solutions and data products; Define and prioritize the Data Science and AI roadmap.
Why It Might Be a Fit
Promote a data-driven culture and encourage evidence-based decision-making; Act in partnership with Analytics, Engineering, Data Governance, and Product teams; Present results and recommendations to technical and executive audiences.
Requirements
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Physics, or related areas
- Minimum 5 years of experience in Data Analysis and Data Science, with at least 2 years in leadership or team management
- Proven experience in developing and implementing Machine Learning models in production, with measurable results
- Mastery of Python, SQL, Spark, and Power BI or equivalent visualization tool
- Solid knowledge in statistical modeling, Machine Learning algorithms, classification, regression, clustering, and attribute engineering
- Practical experience with IA Generative, LLMs, Prompt Engineering, RAG, embeddings, vector banks, fine-tuning, and model evaluation
- Experience with libraries and frameworks such as Scikit-learn, Pandas, PyTorch, and TensorFlow
- Experience with MLOps practices, versioning, implementation, monitoring, and retraining of models, using tools like MLflow
- Knowledge in data architectures, such as Data Lake, Data Warehouse, and Delta Lake, as well as Data Governance
- Experience with A/B testing, experimentation, and defining business metrics
- Excellent communication, analytical vision, and presentation skills
To apply for this job please visit ioasys.gupy.io.
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