Data Scientist

Key Responsibilities

• Model Development & Deployment: Design, build, train, and evaluate predictive machine learning models (classification, regression, clustering) to solve core business problems.
• Data Wrangling & Pipeline Integration: Clean, transform, and feature-engineer structured and unstructured data from disparate sources using SQL and Python/R.
• Exploratory Data Analysis (EDA): Analyze large datasets to identify trends, patterns, anomalies, and opportunities for optimization.
• Collaboration & Business Alignment: Partner closely with product, engineering, and business stakeholders to understand requirements, define metrics, and communicate statistical findings in non-technical terms.
• Model Monitoring & Maintenance: Monitor model performance in production, conduct AB testing, and continuously retrain models to minimize drift.

Required Qualifications & Skills

• Experience: 24 years of industry experience in a Data Scientist or Quantitative Analyst role.
• Education: Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field.
• Programming: Strong proficiency in Python (Pandas, NumPy, Scikit-learn) or R.
• Database & SQL: Advanced proficiency in SQL for extracting, manipulating, and aggregating large-scale datasets.
• Machine Learning Fundamentals: Solid understanding of supervised and unsupervised machine learning algorithms, statistical modeling, hypothesis testing, and evaluation metrics.
• Version Control: Hands-on experience with Git and standard developer workflows.