Skills And Tools:
- Support company business services, sales, leadership and marketing teams with insights gained from analyzing company data.
- Use large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
- Use a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
- Drive business results with their data-based insights.
- Work with a wide range of stakeholders and functional teams.
- Passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Develop company testing framework and test model quality.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Bachelor's degree in computer engineering.
- 5-7 years of experience manipulating data sets and building statistical models.
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
- Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
- Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
- Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
- Strong problem-solving skills with an emphasis on product development.
- 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.
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.
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