Senior Data Scientist

Job Description Roles & Responsibilities Collaborating with client teams to design and implement Generative AI solutions leveraging Machine Learning and Generative AI technologies. Establishing and advocating for best practices within the community. Assessing and choosing the right AI tools and machine learning models for specific projects, including the creation and training of these models with Python and other open-source platforms. Engaging with leadership and key stakeholders to uncover AI opportunities and support strategic development.Description de l'entreprise/ Key responsibilities : - Hold a Bachelor's or Master's degree in Computer Science, Engineering, or a similar discipline. - At least 5 years of professional experience in Data Science and Machine Learning. - Profound knowledge of machine learning, deep learning, and generative AI methodologies. - Experience and expertise in the domain of Generative AI. - Skilled in programming with languages like Python, R, and familiar with TensorFlow, PyTorch, or similar frameworks. - A solid grasp of NLP techniques and familiarity with BERT, GPT, or Transformer models. - Experience in computer vision for tasks such as image recognition, object detection, or image generation. - Practical experience with cloud services like Azure or AWS. - Good command of data engineering tasks such as data collection, cleansing, and preparation. - Awareness of ethical AI principles, emphasizing the importance of fairness, transparency, and accountability in AI technologies. - Effective collaboration with software development and operational teams to ensure the smooth integration and deployment of AI technologies. - Exceptional problem-solving and analytical abilities, capable of converting business needs into technical strategies. - Excellent communication and interpersonal skills, able to work efficiently with team members and stakeholders at all levels. - Demonstrated ability to innovate and keep abreast of the latest trends and research in AI. - Implement ethical AI methodologies to guarantee fairness, clarity, and responsibility in AI models and frameworks. - Lead the adoption of DevOps and MLOps strategies, encompassing ongoing integration, deployment, and surveillance of AI systems. - Employ technologies like Docker, Kubernetes, and Git for constructing and overseeing AI workflows. - Set up monitoring and logging mechanisms to maintain and verify the performance and dependability of AI models. - Work closely with software development and operational teams to ensure smooth integration and deployment of AI models. - Knowledgeable in DevOps and MLOps methodologies, specifically in the areas of continuous integration, deployment, and monitoring of AI models. Desired Candidate Profile Hold a Bachelor's or Master's degree in Computer Science, Engineering, or a similar discipline. At least 5 years of professional experience in Data Science and Machine Learning. Profound knowledge of machine learning, deep learning, and generative AI methodologies. Experience and expertise in the domain of Generative AI. Skilled in programming with languages like Python, R, and familiar with TensorFlow, PyTorch, or similar frameworks. A solid grasp of NLP techniques and familiarity with BERT, GPT, or Transformer models. Experience in computer vision for tasks such as image recognition, object detection, or image generation. Practical experience with cloud services like Azure or AWS. Good command of data engineering tasks such as data collection, cleansing, and preparation. Awareness of ethical AI principles, emphasizing the importance of fairness, transparency, and accountability in AI technologies. Effective collaboration with software development and operational teams to ensure the smooth integration and deployment of AI technologies. Exceptional problem-solving and analytical abilities, capable of converting business needs into technical strategies. Excellent communication and interpersonal skills, able to work efficiently with team members and stakeholders at all levels. Demonstrated ability to innovate and keep abreast of the latest trends and research in AI. Implement ethical AI methodologies to guarantee fairness, clarity, and responsibility in AI models and frameworks. Lead the adoption of DevOps and MLOps strategies, encompassing ongoing integration, deployment, and surveillance of AI systems. Employ technologies like Docker, Kubernetes, and Git for constructing and overseeing AI workflows. Set up monitoring and logging mechanisms to maintain and verify the performance and dependability of AI models. Work closely with software development and operational teams to ensure smooth integration and deployment of AI models. Knowledgeable in DevOps and MLOps methodologies, specifically in the areas of continuous integration, deployment, and monitoring of AI models. Company Industry ConsultingManagement ConsultingAdvisory Services Department / Functional Area IT Software Keywords Senior Data Scientist Get real-time job updates only on our App