Senior Data Scientist
il y a 2 semaines
Job Title: Senior Data Scientist
Contract Length: 6 months
IR35: Outside
Location: Marseille two days per week
Key Responsibilities:
- Predictive Model Development: Design, implement, and iteratively improve predictive models and ML architectures that extract foresight from our time-traversable knowledge graph, focusing on model accuracy, scalability, and interoperability.
- End-to-End Project Leadership: Lead complex, end-to-end predictive projects, from hypothesis generation to deployment, ensuring robust and insightful solutions to meet business needs.
- Model Monitoring and Evaluation: Establish and manage frameworks for continuous model evaluation and monitoring, adapting models to dynamic data and market conditions.
- Stakeholder Engagement: Effectively communicate findings and provide actionable insights to stakeholders, aligning model outputs with business objectives and addressing challenges with data driven solutions.
- Mentorship and Collaboration: Mentor junior data scientists, contributing to the development of the team's analytical capabilities. Collaborate cross-functionally to ensure seamless integration of predictive models into our platform.
What we are looking for:
- PhD in Data Science, Artificial Intelligence, Applied Mathematics, Computer Science, or a related quantitative field.
- Proven expertise in predictive analytics, statistical forecasting, and machine learning (including deep learning).
- Strong programming skills in Python and proficiency with ML frameworks (e.g., TensorFlow, PyTorch, Scikitlearn).
- Advanced experience in data preprocessing, feature engineering, and large-scale data handling (e.g., Spark, Hadoop).
- Hands-on experience with model deployment in cloud environments (e.g., Azure, AWS) and MLOps practices, including model tracking, versioning, and monitoring.
- Familiarity with knowledge graph systems and entity retrieval is highly desirable.
- Strong communication skills, with the ability to present complex technical insights clearly and concisely to both technical and non-technical stakeholders.
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