Data Scientist

As a Senior Data Scientist, you will transform complex datasets into actionable business strategies. This role requires a balance of advanced statistical modeling, machine learning engineering, and the ability to mentor junior staff while navigating a high-impact, cross-functional environment. Key Responsibilities • Predictive Modeling & ML: Develop, fine-tune, and deploy machine learning algorithms, including Random Forests, Neural Networks, and Regression models. You will handle the full lifecycle from feature engineering to production deployment. • Advanced Analytics: Use statistical techniques to perform hypothesis testing, A/B testing, and trend analysis to validate business decisions. • Data Engineering & Integration: Collaborate with IT to access data warehouses, clean messy datasets, and engineer features that enhance model predictive power. • Visualization & Insights: Translate complex findings into compelling stories for both technical and non-technical stakeholders using Tableau, Power BI, Matplotlib, or Seaborn. • Ethics & Governance: Ensure all models and data practices comply with privacy regulations and ethical data standards. • Leadership: Provide mentorship to junior analysts and lead collaboration with domain experts to align data initiatives with organizational goals. Technical Requirements • Experience: 5–10 years in Data Science, with a proven track record in machine learning and statistical analysis. • Programming: High proficiency in Python, R, or Julia. • Data Manipulation: Solid understanding of SQL and database architecture. • Visualization: Expert use of tools like Tableau or Power BI. • Education: Bachelor’s degree in a quantitative field (Statistics, CS, Math, Engineering); Master's or Ph.D. is a plus. • Big Data (Preferred): Familiarity with distributed computing frameworks like Hadoop or Spark.