Data Scientist

As an experienced Data Scientist, you will be responsible for designing, building, and deploying data-driven solutions to enable strategic business decisions and intelligent automation. Your role will involve combining deep analytical expertise with strong programming and applied machine learning skills to transform complex data into actionable insights and scalable models. Key Responsibilities: - Lead end-to-end development of machine learning and statistical models, including data exploration, feature engineering, training, validation, and deployment. - Collaborate with cross-functional teams (Product, Engineering, Business, and AI) to identify opportunities for data science solutions. - Apply advanced techniques in predictive modeling, NLP, computer vision, and deep learning to address complex business challenges. - Implement Generative AI, LLMs, and LangChain frameworks for intelligent automation, content generation, and conversational AI systems. - Build and optimize ETL data pipelines using Python, SQL, and cloud services (AWS, GCP, or Azure). - Conduct A/B testing, model evaluation, and post-deployment monitoring to ensure accuracy and stability. - Visualize insights and communicate findings to stakeholders through dashboards and storytelling tools (e.g., Power BI, Tableau, Plotly). - Mentor junior data scientists and contribute to establishing best practices in model development, versioning, and MLOps. Required Skills & Technologies: - Programming: Python, R, SQL, PySpark - ML/DL Frameworks: Scikit-learn, TensorFlow, PyTorch, Keras - NLP / GenAI: Hugging Face, LangChain, OpenAI APIs, Prompt Engineering - Cloud Platforms: AWS (SageMaker, Bedrock), Azure ML, GCP AI Platform - Data Tools: Pandas, NumPy, Airflow, Kafka, Snowflake, Databricks - Visualization: Power BI, Tableau, Seaborn, Matplotlib, Plotly - MLOps: MLflow, Docker, Kubernetes, Git, CI/CD pipelines - Strong foundation in statistics, probability, linear algebra, and optimization Preferred Qualifications: - Masters or Ph.D. in Computer Science, Data Science, Statistics, or a related field - Proven experience leading data-driven projects end-to-end in a production environment - Experience with LLM fine-tuning, retrieval-augmented generation (RAG), or semantic search - Excellent communication skills and ability to translate technical findings into actionable business insights,