Senior Data Scientist

Role Overview We are seeking a Data Scientist / ML Engineer with strong Python expertise and hands-on experience in modern AI/LLM frameworks and agentic AI development on platforms like Cloudera or Databricks. Key Responsibilities • Develop analytical frameworks and robust measurement strategies across products and services • Design, execute, and analyze complex experiments (A/B testing, user behavior analysis) • Collaborate with Product and Data Engineering teams to build advanced profiling, segmentation, and targeting systems • Translate analytical findings into clear, actionable business insights Required Skills Data Science & Analytics • Strong foundation in data exploration, feature engineering, statistical modeling, and predictive analytics • Proficiency in Python (preferred) or R, with libraries such as NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow • Advanced SQL skills and experience with large-scale data systems Machine Learning & MLOps • End-to-end ML lifecycle experience (build, evaluate, deploy, monitor) • Familiarity with MLOps practices: experiment tracking, versioning, CI/CD, monitoring • Experience with AWS and distributed processing frameworks (e.g., Spark) Generative AI & Agentic Systems • Hands-on experience with LLMs, prompt engineering, and RAG architectures • Experience building agentic workflows (multi-step reasoning, tool use, automation) • Familiarity with frameworks like LangChain, LlamaIndex • Knowledge of embeddings, vector databases, and semantic search AI-Assisted Development • Experience with AI-driven coding workflows (code generation, debugging, evaluation loops) • Ability to integrate LLMs with APIs, tools, and enterprise systems Business & Collaboration • Strong communication skills to convey complex insights to diverse stakeholders • Ability to work with ambiguous data and deliver business-aligned solutions • Experience in marketing analytics or customer analytics is a plus • Proven ability to collaborate across product, engineering, and business teams