Job Description & Summary
Main Missions: Define and implement the Data Science strategy in line with business challenges. Identify, prioritize, and frame high-impact use cases. Apply advanced machine learning, deep learning, and NLP techniques to develop predictive and prescriptive models. Interpret and communicate results clearly and accessibly to stakeholders. Develop massive data processing assets, integrating GenAI solutions to improve quality and automation. Industrialize projects via MLOps practices (CI/CD, monitoring, versioning). Automate business processes thanks to AI and GenAI.
Mentoring & Leadership: Supervise, train, and develop the skills of a team of junior Data Scientists. Structure projects and establish good development and collaboration practices. Ensure follow-up of deliverables, quality of deliverables, and documentation. Collaborate closely with Data Engineering, IT, and business teams.
Eligibility / Qualification Required:
Required Technical Skills:
- Experience: Minimum 6 years in a similar role, with a strong project and leadership dimension.
- Languages & Tools: Python, R, Git, Airflow, Kubernetes, Docker.
- Cloud & Big Data: Azure, Databricks, Azure ML, Hadoop, Spark.
- Machine Learning & AI: pandas, scikit-learn, TensorFlow, PyTorch, NLP.
- Databases: SQL, MySQL, NoSQL.
- Visualization: Power BI, Snowflake, DBT, Matplotlib, Seaborn.
Desired Profile:
- Solid technical expertise and ability to popularize complex concepts.
- Natural leadership, sense of organization, and results orientation.
- Innovative spirit, curiosity, and ability to challenge classical approaches.
- Experience in agile and collaborative environments.
General Conditions:
No general conditions were provided in the job description.
How to Apply:
No application instructions were provided in the job description.
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