Data ScientistP

We are seeking an experienced Data Scientist to design, build, and deploy data-driven solutions that power strategic business decisions and intelligent automation. The ideal candidate combines deep analytical expertise with strong programming and applied machine learning skills, capable of transforming complex data into actionable insights and scalable models.. Key Responsibilities:. Lead end-to-end development of machine learning and statistical models — from data exploration and feature engineering to 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 solve complex business problems.. 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).. Perform A/B testing, model evaluation, and post-deployment monitoring to ensure accuracy and stability.. Visualize insights and communicate findings to stakeholders using 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:. Master’s 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. Show more Show less