Data Scientist

Posted: 2026-09-29

Data Scientist

Job requirements Experience Range: With at least 4 years of hands-on experience in advanced data science, including statistical analysis and machine learning, and up to 6 years in similar roles Key Responsibilities:

- Design and implement robust statistical models using advanced hypothesis testing, regression, and forecasting techniques to deliver actionable business insights

- Develop and optimize machine learning algorithms for classification, prediction, and probabilistic graph models utilizing Python, PySpark, and R

- Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to support data-driven decision-making

- Build, train, and deploy scalable models using ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet

- Apply advanced time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to analyze trends and predict outcomes

- Streamline model deployment and lifecycle management in production environments using KubeFlow and BentoML

- Implement and validate data quality checks with Great Expectations and Evidently AI to ensure dataset integrity

- Present complex data findings to stakeholders, translating insights into actionable recommendations that drive business outcomes

- Advanced application of hypothesis testing methodologies, including T-Test and Z-Test

- Expert-level regression analysis (linear and logistic) for predictive modeling

- Proficient programming in Python and PySpark for data manipulation and model development

- Extensive experience with statistical analysis using SAS and SPSS

- Hands-on expertise in probabilistic graph models for complex data relationships

- Mastery of time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)

- Implementation of classification algorithms such as decision trees and support vector machines (SVM)

- Deep familiarity with ML frameworks: TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet