Data Scientist

Key Responsibilities: • Understand warehouse concepts and business intelligence reporting. • Design databases, data models, and manage data integration/extraction. • Create visualizations using tools such as Power BI (or Tableau). • Write Python code for data wrangling, statistical analysis, and model development. • Apply statistical modeling techniques (e.g., logistic regression, SVM) to solve business problems. • Independently translate problem statements into analytical solutions and lead implementation. • Collaborate with stakeholders across the organization to identify data‑driven opportunities. • Quickly learn new languages, tools, or platforms as needed. • Conceptualize, design, and deliver high‑quality solutions and insightful analyses. What We're Looking For: • Expert‑level proficiency in Python and SQL. • Hands‑on experience with relational databases such as SQL Server or Oracle. • Experience managing the end‑to‑end data science pipeline: problem scoping, data collection, exploratory data analysis, modeling, insight generation, visualization, and model monitoring/maintenance. • Strong problem‑solving skills with the ability to break complex problems into manageable parts. • Intermediate to advanced knowledge of machine learning, probability theory, statistics, and algorithms, including regression, tree‑based methods, SVM, random forests, XGBoost, time‑series modeling, dimensionality reduction, clustering, and deep learning. • Proficiency with visualization tools (Power BI preferred; Tableau also acceptable). Preferred (Good to Have): • Experience with emerging technologies such as deep learning, natural language processing, or recommender systems.