Manage and execute entire project from start to finish (problem solving, data gathering, data manipulation, predictive modeling, and key stakeholder engagement)
Demonstrate technical knowledge on feature engineering, effective exploratory data analysis, and building statistical models
Implement code (Python, R, Scala, SQL, etc.) for analyzing data and building machine learning and econometric models to solve specific business problems
Translate analytic insights into actionable recommendations
Contribute to the scientific roadmap
Research, learn, and adapt new modeling techniques and procedures to solve complex business problems
Build a common data science infrastructure that will house statistical models and enable scientists to run experiments on a large variety of project
Produce and maintain technical documents

Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field; or data science practitioner for 3+ years
Solid experience in descriptive analytics (reporting, querying, scorecards, dashboard building, visualization, presentations, etc.)
Experience in data mining and data engineering techniques (gathering, preparing, cleansing, and transforming data) to find patterns and build models
2+ years of experience in predictive analytics (statistical data modeling, predicting what customers would do, how customers would respond to marketing campaigns, how client experience would improve, etc.)
Experience in supervised methods (classification, regression, causal modeling) and unsupervised methods (clustering, co-occurrence grouping, profiling)
Experience programming in R, Scala, Python (Django, Flask, Pyramid, etc.), or similar languages and maintaining code repositories
Experience formulating and testing hypotheses using tools like Jupyter notebooks, R, Julio, etc.
Create prototype machine learning or statistical models using open-source packages, such as SciKit Learn, PyTorch, Tensorflow, Stan, or equivalent
Excellent verbal and written communication skills

Data Analyst

Key skills