Help create analytics solutions from developing and delivering code and models, to finding meaningful insights in results, and translating them into actionable plans for stakeholders
Work with stakeholders to identify opportunities to benefit from university data to develop business solutions
Craft solutions tailored to client needs using programming languages such as R and Python and platforms
Causal Inference, Bayesian Optimization, Technical Geospatial and Analysis Methodologies such as
.Analytics, Natural Language Processing
Exploration and analysis of data from databases to improve and develop services and business strategies
Evaluate the effectiveness and accuracy of new data sources and data collection techniques
Develop custom data models and algorithms to apply to datasets
Coordinating with the different work teams to implement the models and monitor the results
Develop processes and tools to monitor and analyze model performance and data accuracy
Present information using data visualization techniques
Requirements
Must have a Bachelor's degree in Statistics/Computer Science or equivalent
Data Analytics and Machine Learning. At least 7 years of practical experience in data science. 7.2.2
Experience in querying databases and using statistical programming languages SLQ, Python, R, etc
Decision Tree Clustering, such as Machine Learning Familiarity with a variety of machine learning techniques 7.2.4
.Artificial Neural Networks, Learning
Knowledge of advanced statistical techniques and concepts, Properties of Distributions, Regression
Knowledge and experience in statistical and data mining techniques: Random Forest, GLM/Regression,
Etc., Social Network Analysis, Text Mining, Trees, Boosting
Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling,
Regression, Simulation, Scenario Analysis, Clustering, Decision Trees, and Neural Networks