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Data Scientist Manager
Posted 15 days agoViewed
💎 Seniority level: Manager, 6+ years
🔍 Industry: HealthTech
🏢 Company: Idoven
🗣️ Languages: English
⏳ Experience: 6+ years
Requirements:
- Master's or PhD in a quantitative field with a focus on Deep Learning.
- 6+ years of experience in developing, optimizing, and deploying Deep Learning models in production.
- Strong expertise in signal processing, data balancing, model debugging, and performance optimization.
- Proficiency in TensorFlow or PyTorch, Python, and ML libraries (NumPy, Scikit-learn, Pandas).
- Experience leading and mentoring teams, driving collaboration, and managing machine learning pipelines.
- Strong project management and communication skills, with the ability to align technical goals with business objectives.
Responsibilities:
- Lead and mentor a team of data scientists and engineers, providing technical guidance and fostering professional growth.
- Continuously research and integrate emerging Deep Learning techniques, including representation learning, self-supervised learning, generative models, and novel neural network architectures, to drive innovation.
- Analyze, enhance, and scale Deep Learning models for complex signal processing tasks, ensuring high accuracy, efficiency, and generalization.
- Oversee the implementation of data balancing, augmentation, and synthetic data generation techniques to improve model robustness.
- Drive model optimization efforts, leveraging techniques such as fine-tuning, distillation, quantization, and distributed training for improved performance.
- Spearhead automation initiatives for data preprocessing, model training, and deployment pipelines to accelerate development cycles and ensure efficiency.
- Collaborate closely with engineers, domain experts, and stakeholders to ensure technical solutions align with real-world applications and business goals.
- Advocate for best practices in AI model development, validation, and deployment, ensuring high-quality and scalable solutions.
- Stay abreast of the latest advancements in Deep Learning, signal processing, and AI to maintain a cutting-edge approach to research and development.
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