Data Scientist

Role Overview: Data Scientist Location: Remote/ Indore/ Mumbai/ Chennai/ Gurugram Experience: Min 5 Years Work Mode: Remote Notice Period: Max. 30 Days (45 for Notice Serving) Interview Process: 2 Rounds Interview Mode: Virtual Face-to-Face Interview Timeline: 1 Week Industry: Must be from a BPO/ KPO/ Shared Services or Healthcare Org. Key Responsibilities: - AI/ML Development & Research - Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems. - Implement and optimize Large Language Models (LLMs) and Generative AI solutions for real-world applications. - Build agent-based AI systems with autonomous decision-making capabilities. - Conduct cutting-edge research on emerging AI technologies and explore their practical applications. - Perform model evaluation, validation, and continuous optimization to ensure high performance. - Cloud Infrastructure & Full-Stack Development: - Architect and implement scalable, cloud-native ML/AI solutions using AWS, Azure, or GCP. - Develop full-stack applications that seamlessly integrate AI models with modern web technologies. - Build and maintain robust ML pipelines using cloud services (e.G., SageMaker, ML Engine). - Implement CI/CD pipelines to streamline ML model deployment and monitoring processes. - Design and optimize cloud infrastructure to support high-performance computing workloads. - Data Engineering & Database Management - Design and implement data pipelines to enable large-scale data processing and real-time analytics. - Work with both SQL and NoSQL databases (e.G., PostgreSQL, MongoDB, Cassandra) to manage structured and unstructured data. - Optimize database performance to support machine learning workloads and real-time applications. - Implement robust data governance frameworks and ensure data quality assurance practices. - Manage and process streaming data to enable real-time decision-making. - Leadership & Collaboration - Mentor junior data scientists and assist in technical decision-making to drive innovation. - Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to develop solutions that align with organizational goals. - Present findings and insights to both technical and non-technical audiences in a clear and actionable manner. - Lead proof-of-concept projects and innovation initiatives to push the boundaries of AI/ML applications. Required Qualifications: - Education & Experience - Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field. - 5+ years of hands-on experience in data science and machine learning, with a focus on real-world applications. - 3+ years of experience working with deep learning frameworks and neural networks. - 2+ years of experience with cloud platforms and full-stack development. - Technical Skills - Core AI/ML - Machine Learning: Proficient in Scikit-learn, XGBoost, LightGBM, and advanced ML algorithms. - Deep Learning: Expertise in TensorFlow, PyTorch, Keras, CNNs, RNNs, LSTMs, and Transformers. - Large Language Models: Experience with GPT, BERT, T5, fine-tuning, and prompt engineering. - Generative AI: Hands-on experience with Stable Diffusion, DALL-E, text-to-image, and text generation models. - Agentic AI: Knowledge of multi-agent systems, reinforcement learning, and autonomous agents. - Technical Skills - Development & Infrastructure - Programming: Expertise in Python, with proficiency in R, Java/Scala, JavaScript/TypeScript. - Cloud Platforms: Proficient with AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI. - Databases: Proficiency with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB). - Full-Stack Development: Experience with React/Vue.Js, Node.Js, FastAPI, Flask, Docker, Kubernetes. - MLOps: Experience with MLflow, Kubeflow, model versioning, and A/B testing frameworks. - Big Data: Expertise in Spark, Hadoop, Kafka, and streaming data processing. Non Negotiables: - Cloud Infrastructure - ML/AI solutions on AWS, Azure, or GCP - Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.) - Implement CI/CD pipelines for ML model deployment and monitoring - Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.) - Machine Learning: Scikit-learn - Deep Learning: TensorFlow - Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript - Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda) - Vector databases and embeddings (Pinecone, Weaviate, Chroma) - Knowledge of LangChain, LlamaIndex, or similar LLM frameworks. - Industry: Must be a BPO or Healthcare Org.