Data Scientist

Role Overview: Data Scientist Location: Remote/ Indore/ Mumbai/ Chennai/ GurugramExperience: Min 5 YearsWork Mode: RemoteNotice Period: Max. 30 Days (45 for Notice Serving)Interview Process: 2 RoundsInterview Mode: Virtual Face-to-FaceInterview Timeline: 1 WeekIndustry: Must be from a BPO/ KPO/ Shared Services or Healthcare Org.Key Responsibilities:AI/ML Development & ResearchDesign, 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 ManagementDesign 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 & CollaborationMentor 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 & ExperienceMaster’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/MLMachine 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 & InfrastructureProgramming: 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 GCPBuild and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)Implement CI/CD pipelines for ML model deployment and monitoringWork with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)Machine Learning: Scikit-learnDeep Learning: TensorFlowProgramming: Python (expert), R, Java/Scala, JavaScript/TypeScriptCloud 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.