We are looking for a Data Scientist who will support our product, sales, leadership and marketing teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using 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. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company data to drive optimization and improvement of sales, operations, 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 A/B testing framework and test model quality.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Strong problem solving skills
- Experience using statistical computer languages (R, Python, SLQ, 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
- Excellent written and verbal communication skills for coordinating across teams
- A drive to learn and master new technologies and techniques
- Coding knowledge and experience with several languages: C, C++, Java,
- 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 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.
Ferguson is dedicated to providing meaningful benefits programs and products to our associates and their families—geared toward benefits, wellness, financial protection and retirement savings. Ferguson offers a competitive benefits package which includes: medical, dental, vision, retirement savings with company match, paid leave (vacation, sick, personal and holiday), employee assistance programs, associate discounts, community involvement opportunities and much more!
The Company is an equal opportunity employer as well as a government contractor that shall abide by the requirements of 41 CFR 60-300.5(a), which prohibits discrimination against qualified protected Veterans and the requirements of 41 CFR 60-741.5(A), which prohibits discrimination against qualified individuals on the basis of disability.