Gen AI Data Scientist

Data Scientist – Gen AI, ML, Deep Learning, NLP & Graph Intelligence

Experience: 6-9 Years
Location: Pune
Employment Type: Full-time

Role Overview:

We are seeking a highly experienced and forward-thinking Senior Data Scientist to lead cutting-edge initiatives in Generative AI, Machine Learning, and Graph Intelligence. This role demands deep expertise in Neo4j, AWS Neptune, NLP, and LLM frameworks, with a strong foundation in predictive analytics and solution architecture. You will be instrumental in designing scalable, intelligent systems that transform data into actionable insights.

Key Responsibilities:

We are seeking an experienced Data Scientist for Cyber Analytics & AI team to design, build, and deploy machine learning and deep learning solutions for client engagements. You’ll lead end-to-end model development: data preparation, model design with PyTorch or TensorFlow, scalable training with distributed engines and production hand-off—working closely with engineers, consultants, and business stakeholders.

This position requires a strong foundation in machine learning, deep learning, predictive modeling, and multi-modal AI and proven proficiency in Python and model deep learning frameworks.

• Design, develop, and validate ML/DL models using PyTorch or TensorFlow for real business problems.

• Implement production-ready code in Python and collaborate with engineering teams for deployment.

• Process and transform large datasets using distributed computing frameworks (Dask/Ray).

• Lead model training, hyperparameter tuning, experiment tracking, and performance evaluation.

• Build reusable pipelines and components for feature engineering, training, and inference.

• Translate business use cases into technical solutions and present model findings to non-technical stakeholders.

• Ensure model reliability, monitoring, and compliance with governance and security requirements.

• Mentor junior team members; contribute to best practices, code reviews, and architecture decisions.

Required qualifications

• 3–5 years hands-on experience building ML or deep learning models using PyTorch or TensorFlow.

• Strong .Net & Python programming skills; experience producing clean, well-documented, version-controlled code.

• Experience with distributed computing engines (e.g., Spark/PySpark, Dask, Ray) for large-scale data processing.

• Solid understanding of core ML concepts: supervised/unsupervised learning, neural network architectures, regularization, evaluation metrics, and model validation.

• Experience with model training workflows, hyperparameter tuning tools, and ML tooling (e.g., MLflow, TensorBoard).

• Proven communication and interpersonal skills and experience working in cross-functional teams.

Preferred (nice-to-have)

• Experience with graph databases and graph ML (Neo4j, Amazon Neptune) or libraries like PyTorch Geometric.

• Background in cybersecurity use cases (threat detection, anomaly detection/fraud analytics).

• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization/orchestration (Docker, Kubernetes).

• Exposure to MLOps practices: CI/CD for models, model monitoring, automated retraining.

• Advanced degree (MS degree or higher) in Computer Science, Statistics, Data Science, Applied Mathematics, computational sciences, or related field.

Preferred Qualifications:

• Bachelor's or Master’s or Ph.D. in Computer Science, Data Science, AI, or a related field.
• Experience with graph neural networks, semantic search, or knowledge graph reasoning.
• Exposure to ethical AI, data privacy, and responsible AI practices.
• Contributions to open-source AI/ML projects or research publications.