Senior Data Scientist

- Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related discipline. - 6–8 years of practical experience in applied machine learning, predictive modeling, and generative AI, ideally with clinical and GIS datasets. - Proficient in programming languages such as Python, R, and Java; strong SQL skills. - In-depth knowledge of ML frameworks (TensorFlow, PyTorch) and data manipulation libraries (pandas, dplyr). - Familiarity with data visualization tools like Streamlit/Dash, matplotlib, ggplot2, Plotly. - Understanding of Generative AI techniques, RAG pipelines, and agentic frameworks such as LangChain or LlamaIndex. - Experience with cloud-based AI/ML platforms (Azure, Databricks, or similar). - Solid grounding in statistical modeling, hypothesis testing, regression analysis, time-series forecasting, and Bayesian methods. - Knowledgeable in supervised and unsupervised learning, ensemble methods, deep learning structures, process mining, and NLP techniques. - Awareness of model evaluation metrics, bias/variance trade-offs, and methods for interpretability and fairness. - Exceptional communication skills with the ability to convey complex ideas to various stakeholders. Strong multitasking and project management capabilities.