Data Scientist - R01570831

Job requirements

Experience Range: With 4 to 6 years of experience in advanced data science roles, including hands-on involvement in machine learning and statistical modeling projects Key Responsibilities:

• Develop and implement Next Best Offer models and advanced data science solutions to drive business objectives and enhance customer engagement
• Apply statistical techniques such as hypothesis testing, t-tests, z-tests, and regression methods to extract actionable insights and support data-driven decision-making
• Build, validate, and optimize machine learning models using Python, PySpark, and R to ensure high accuracy and reliability
• Leverage probabilistic graph models and classification algorithms, including decision trees and support vector machines, to address complex business challenges
• Optimize and automate machine learning pipelines for scalable deployment using KubeFlow and BentoML, improving operational efficiency
• Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to inform business strategies
• Monitor model performance using evaluation metrics and recommend data-driven improvements to maintain model effectiveness
• Collaborate with cross-functional teams to translate business requirements into impactful data science solutions

• Python
• PySpark
• SAS
• SPSS
• R
• Probabilistic graph models
• Regression methods (linear and logistic)
• Forecasting methods (exponential smoothing, ARIMA, ARIMAX)
• TensorFlow
• PyTorch
• Scikit-learn
• CNTK
• Keras
• MXNet
• Decision trees
• Support Vector Machines (SVM)
• Distance metrics (Hamming, Euclidean, Manhattan)
• KubeFlow
• BentoML

• Experience with Great Expectations and Evidently AI for model validation and monitoring
• Expertise in deploying machine learning models in cloud-based environments
• Knowledge of advanced ensemble methods and boosting algorithms
• Familiarity with A/B testing and experimental design
• Background in recommendation systems and personalization algorithms

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a quantitative discipline relevant to data science
• Certification in Machine Learning or Data Science from a recognized institution such as Coursera, edX, or DataCamp
• Relevant certification in statistical analysis or analytics, such as SAS Certified Statistical Business Analyst