Senior Data Scientist

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 expertise in Deep Learning, NLP, and traditional ML will be essential in the following key responsibilities: - Design, develop, test, and deploy machine learning and deep learning models using state-of-the-art algorithms. - Develop state-of-the-art deep learning models for audio projects. - Research and experiment with deep learning architectures (CNNs, RNNs, LSTMs, Transformers, etc.) for structured and unstructured data. - Work on end-to-end AI/ML solutions including data acquisition, feature engineering, model development, and deployment. - Build and improve reusable model pipelines, frameworks, and data processing tools. - Define and enforce best practices for Machine Learning and MLOps, including model versioning, testing, and deployment. - Collaborate closely with product managers and business stakeholders to translate data-driven insights into actionable strategies. - Mentor junior team members and promote knowledge sharing across teams. Qualifications required for this role include: - Experience: 5-8 years 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. - MLOps & Deployment: Familiarity with Flask/FastAPI, Docker, and cloud environments (AWS, GCP, or Azure) for deploying models. - Data & Visualization: Proficient with Pandas, NumPy, Scikit-learn, and visualization tools such as Matplotlib or Plotly. - Soft Skills: Excellent communication and storytelling skills with the ability to present complex results clearly. Proven ability to work collaboratively in cross-functional teams. Strong problem-solving skills and initiative in driving innovation.,