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 & 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.