Senior Data Scientist - Deep Learning

As a Senior Data Scientist with Deep Learning experience, your role will involve designing, building, and deploying advanced machine learning models for real-world applications. You will collaborate with research, product, and engineering teams to deliver impactful AI-driven solutions. Your key responsibilities will include: - Designing, developing, testing, and deploying machine learning and deep learning models using state-of-the-art algorithms. - Developing state-of-the-art deep learning models for audio projects. - Researching and experimenting with deep learning architectures such as CNNs, RNNs, LSTMs, Transformers, etc., for structured and unstructured data. - Working on end-to-end AI/ML solutions including data acquisition, feature engineering, model development, and deployment. - Building and improving reusable model pipelines, frameworks, and data processing tools. - Defining and enforcing best practices for Machine Learning and MLOps, including model versioning, testing, and deployment. - Collaborating closely with product managers and business stakeholders to translate data-driven insights into actionable strategies. - Mentoring junior team members and promoting knowledge sharing across teams. In terms of qualifications, you should have: - At least 5-8 years of experience in Data Science or Machine Learning with hands-on deep learning expertise. - Strong knowledge of machine learning algorithms, optimization techniques, and statistical modeling. - Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras. - Strong understanding of neural networks, CNNs, LSTMs, transformers, and other deep learning architectures. - Experience using Python and ML/NLP libraries such as SpaCy, NLTK, Gensim, CoreNLP, and OpenNLP. - Familiarity with data preprocessing techniques and tools for audio data. - Familiarity with MLOps & Deployment tools like Flask/FastAPI, Docker, and cloud environments (AWS, GCP, or Azure) for deploying models. - Proficiency in data manipulation using Pandas, NumPy, Scikit-learn, and visualization tools such as Matplotlib or Plotly. Your soft skills should include excellent communication and storytelling abilities, the capacity to present complex results clearly, a proven ability to work collaboratively in cross-functional teams, and strong problem-solving skills with an initiative in driving innovation.,