Principal Data Scientist - R01568403

Job requirements

• Experience Range: 15 - 18 years of experience in advanced data science roles, with extensive leadership in designing and deploying statistical and machine learning solutions

Key Responsibilities

• Design and implement robust statistical models and machine learning algorithms for large-scale data analysis and predictive analytics
• Lead end-to-end development of data science projects, including hypothesis testing, regression analysis, classification, and forecasting
• Collaborate with cross-functional teams to define business requirements, translate them into analytical solutions, and drive measurable impact
• Optimize and automate data pipelines using Python, PySpark, and R, ensuring efficient data processing and feature engineering
• Develop, validate, and maintain probabilistic graph models and advanced statistical computing frameworks
• Utilize industry-leading ML frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn to build, train, and deploy models
• Establish rigorous model evaluation and monitoring processes using tools like Great Expectations and Evidently AI
• Mentor and guide junior data scientists, fostering technical excellence and continuous learning within the team

Required Skills

• Expertise in hypothesis testing, including T-Test and Z-Test methodologies
• Advanced proficiency in regression techniques (linear and logistic)
• Strong programming skills in Python, PySpark, and R/R Studio
• Hands-on experience with SAS and SPSS for statistical analysis and computing
• In-depth knowledge of probabilistic graph models
• Experience with forecasting methods such as Exponential Smoothing, ARIMA, and ARIMAX
• Practical use of classification algorithms including Decision Trees and Support Vector Machines (SVM)
• Proficiency with ML frameworks: TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet
• Familiarity with distance metrics (Hamming, Euclidean, Manhattan)
• Working knowledge of Kubeflow and BentoML for model deployment and orchestration

Preferred Skills

• Experience implementing advanced model monitoring with Evidently AI
• Expertise in data pipeline automation and orchestration using Kubeflow
• Knowledge of emerging ML frameworks and architectures
• Experience with large-scale distributed computing environments
• Strong background in statistical validation and reproducibility best practices

Desired Qualifications

• Master's or PhD degree in Data Science, Statistics, Computer Science, Mathematics, or a related field
• Relevant certifications in machine learning, statistical analysis, or advanced data science

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