Data Scientist

Master s degree or higher in a relevant analytical field.
Highly proficient with SQL
Hands-on experience with software development using Python Pandas, and Numpy
Experience solving problems using a variety of statistical and machine learning techniques.
Hands-on experience using statistical or machine learning frameworks to solve a variety of real-world problems (e.g., statsmodels, scikit-learn, PyTorch, TensorFlow, etc).
Knowledge of methods like Logistic Regression, Time Series Analysis, GLMs, Mixed Modeling, Multivariate Statistics, Predictive Modeling, Decision Trees, Gradient-Boosted Trees, Random Forests, and Neural Networks.
Proactive approach to identifying problems and developing innovative solutions.
Experience with version control in GitHub

Added bonus if you have (Preferred):
Familiarity with CI/CD practices to streamline model deployment and code management.
Hands-on experience with cloud-based machine learning platforms (e.g., AWS SageMaker or Azure ML) to leverage scalable computing resources and tools.
Demonstrated ability to lead through influence, effectively navigating and prioritizing complex cross-departmental projects to drive impactful change.
Capability to replace and bridge existing legacy infrastructure and processes.
Experience with the Snowflake, Netezza, or Microsoft SQL environment
Experience with SAS programming language
Understanding of cashflow financial analysis and its implications for business strategy is highly desirable.