Senior Data Scientist

Job description

**Senior Data Scientist** We are seeking a Senior Data Scientist who is passionate about solving complex business problems using both classical machine learning and cutting-edge Generative AI techniques. The ideal candidate will have strong hands-on experience in Python, SQL, and advanced ML algorithms, along with expertise in LLMs, transformers, and generative pipelines. You will collaborate with cross-functional teams including product, engineering, and business stakeholders to drive innovation and data-driven strategies across forecasting, optimization, and AI-powered solutions. **Key Responsibilities:** - **Predictive Modeling**: Design, build, and deploy models for demand forecasting, dynamic pricing, inventory optimization, and other business-critical use cases. - **Generative AI Solutions**: Develop and fine-tune LLMs (e.g., GPT, LLaMA, Claude, PaLM) for tasks such as summarization, content generation, semantic search, and question answering. - **End-to-End Pipelines**: Build scalable workflows including prompt engineering, model training/fine-tuning, evaluation, and deployment. - **Data Engineering Collaboration**: Partner with data engineers to ensure seamless integration of models into production systems. - **RAG Development**: Use frameworks like LangChain, LlamaIndex, and vector databases (FAISS, Pinecone, Weaviate) to build retrieval-augmented generation pipelines. - **Insights & Storytelling**: Translate business problems into analytical frameworks, present findings to leadership using compelling visualizations, and provide actionable recommendations. - **Research & Innovation**: Stay current with the latest techniques in ML, statistics, operations research, and GenAI. - **Mentorship**: Lead and mentor junior data scientists and analysts when required. **Required Skills and Experience:** - **Experience**: 5+ years in Data Science/AI roles, with strong business impact; 2+ years in Generative AI/LLMs. - **Programming**: Strong Python (pandas, scikit-learn, statsmodels, Hugging Face, PyTorch/TensorFlow) and SQL skills. - **ML Expertise**: Deep understanding of regression, classification, clustering, time series forecasting, and generative techniques. - **GenAI Skills**: Experience with prompt engineering, fine-tuning, few-shot learning, and orchestration frameworks (LangChain, LlamaIndex). - **Data Handling**: Experience with large datasets and distributed computing tools (Spark, Hadoop). - **Visualization**: Familiarity with Tableau, Power BI, matplotlib, seaborn. - **Deployment**: Experience deploying models in cloud/hybrid environments (Azure, AWS, GCP) and knowledge of MLOps best practices. **Preferred Qualifications:** - **Education**: Masters or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or related fields. - **Domain Expertise**: Experience in retail, e-commerce, manufacturing, or logistics. - **Optimization**: Exposure to PuLP, OR-Tools, Gurobi. - **GenAI Platforms**: Experience with OpenAI, Anthropic, Meta AI, or Google Cloud GenAI APIs. - **Applications**: Background in chatbot development, co-pilot solutions, or enterprise GenAI applications. - **Contributions**: Publications or open-source contributions in ML/GenAI.