Responsibilities for Data Scientist
- Develop methods to create ongoing anomaly detectionwith click stream data.
- Develop methods to create propensity models with click stream data.
- Work with stakeholders throughout the organization to identify opportunities for leveraging click stream data.
- Mine and analyze data from multiple sources including database and real time streaming.
- Assess the effectiveness and accuracy of data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
Qualifications for Data Scientist
- Strong problem solving skills with an emphasis on product development.
- Experience using statistical computer languages (R, Python, SLQ, Java, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- A drive to learn and master new technologies and techniques.
- We're looking for someone with 5-7+ years of experience manipulating data sets and building statistical models, has a BS or higher in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools or their functional equivalent:
- Coding knowledge and experience with several languages: Java, R, Python, SQL
- Knowledge and experience in statistical and data mining techniques: Anomaly detection, propensity modeling, etc.
- Experience querying databases and using statistical computer languages: Java, R, Python, SLQ, etc.
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
- Experience visualizing/presenting data for stakeholders using: Business Objects, Tableau, D3, chart.Js, etc.