Description :

We are seeking a highly skilled Senior Data Scientist to design, build, and optimize intelligent systems that power data-driven decision-making and advanced natural language understanding capabilities. The ideal candidate will possess deep technical expertise in Machine Learning (ML) and Natural Language Processing (NLP/NLU), combined with a strong software engineering mindset to take models from research to scalable production systems.

You will collaborate closely with product managers, data engineers, and software developers to deliver high-impact solutions in a dynamic, fast-paced environment.

Key Responsibilities :

1. Research & Innovation :

- Stay abreast of cutting-edge developments in NLP, NLU, and AI research.

- Explore and prototype advanced models across domains such as topic modeling, machine translation, named entity recognition (NER), semantic understanding, and knowledge graph construction.

- Conduct applied research to identify emerging techniques that can be productized for business impact.

2. System Design & Architecture :

- Architect and maintain Python-based AI/ML applications, ensuring scalability, maintainability, and robustness.

- Participate in product design discussions, influencing technical decisions with data-driven insights and feasibility assessments.

- Define system-level data flows and ensure efficient integration between model outputs and product interfaces.

3. Implementation & Optimization :

- Enhance existing ML features and proactively design new algorithms aligned with product roadmaps.

- Improve model performance, training efficiency, and inference latency through optimization, fine-tuning, and pipeline automation.

- Collaborate in Agile development cycles and ensure timely delivery of high-quality solutions.

4. Collaboration & Cross-Functional Impact :

- Partner with product managers and business stakeholders to define measurable success metrics.

- Work closely with other data scientists, ML engineers, and developers to establish best practices for model development, versioning, and deployment.

- Communicate analytical findings in a clear, actionable manner to technical and non-technical audiences.

5. Leadership & Mentorship :

- Conduct technical reviews, ensure code and model quality, and uphold engineering excellence.

- Provide guidance and mentorship to junior data scientists, fostering a culture of continuous learning and experimentation.

Required Qualifications :

Education : B.Tech / M.Tech / M.Sc / Ph.D. in Computer Science, Data Science, AI/ML, or a related discipline.

Experience :

- 3+ years in Machine Learning, with at least 2 years focused on NLP/NLU applications.

- Proven experience in model development, deployment, and lifecycle management in production-grade systems.

- Deep knowledge of ML/DL frameworks : TensorFlow, Keras, PyTorch, and solid understanding of architectures like CNN, RNN/LSTM/GRU, Transformers, Transfer Learning, and Ensemble Learning.

- Proficiency with Python and libraries such as NumPy, pandas, scikit-learn, spaCy, HuggingFace Transformers, or NLTK.

- Strong grasp of classical ML concepts: LDA, SVD, Clustering, Regression, and Dimensionality Reduction.

Preferred Skills :

- Experience with Flask, uWSGI, Celery, Docker, and MySQL for ML service deployment and backend integration.

- Familiarity with AWS ML ecosystem (SageMaker, EC2, S3, Lambda) or Azure ML.

- Exposure to MLFlow, DVC, or similar tools for ML lifecycle and experiment tracking.

- Solid understanding of DevOps for ML (MLOps), CI/CD, and containerization.

- Excellent analytical, problem-solving, and communication skills.