Basic Job Functions:
This position supports organizational strategy and operations through design and statistical analysis of business initiatives and experiments. Works with business partners to understand what the business needs and issues are to address. Applies advanced knowledge of statistics and data mining (e.g., predictive modeling, simulation) or other mathematical techniques to recognize patterns and create insights from business data. Designs, develops, and evaluates statistical and predictive models that lead to business solutions. Serves as lead statistician for the unit, providing expertise, oversight and guidance on statistical analysis efforts. Communicates findings and recommendations to management across different departments. Supports implementation efforts.
Education:
Bachelor’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 6+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development
Master’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 4+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development
PhD degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 3+ years of relevant work experience in in Data Science, Artificial Intelligence or Machine Learning algorithm development
Required Skills/Competencies:
Demonstrated experience with programming languages and statistical software tools (Python, SAS, R, JMP or similar), relational databases (SQL server), data analysis and visualization software (preferably PowerBI, SAS).
Demonstrated experience with standard data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly
Demonstrated experience with the machine learning model stack (regression, classification, neural networks, time series) and packages (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels)
Demonstrated experience of the machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability.
Demonstrated experience with utilizing advanced descriptive statistics and analysis techniques (such as forecasting, analysis of variance, t-tests, categorical data analysis, nonparametric data analysis, cluster analysis, factor analysis and multivariate statistical analysis) design business experiments and measure the impact of business actions.
Demonstrated experience with computer vision models (e.g. image classification, object detection, and segmentation)
Demonstrated experience working with various business partners to scope and design the statistical framework for business solutions, and socialize and help integrate results.
Strong communication skills to work with groups, and experience with communicating business implications of complex data relationships and results of statistical models to multiple business partners.
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