Process Analyst

We are looking for a Data Scientist who will support our pricing and business teams with insights and real-time price recommendations using company and market data. The ideal candidate is adept at using large and limited data sets to drive insights-based pricing.Theymust 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 data sets and working with stakeholders to improve business outcomes.

KeyResponsibilities:

• Take end-to-end responsibility in analyzinglarge amountsof data, creating complex models, improving theiraccuracyand deploying these models.
• Deliver onpricing Annual Operating plan through surfacing insights to improve margins and revenue.
• Work with stakeholders throughout thepricing and businessteamstoidentifyopportunities forleveragingcompany data to drive business solutions.
• Mine and analyze data from company databases to drive optimization and improvement ofpricing recommendations.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Build real-timeGenAIpricing models.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase andoptimizerevenueand margingeneration, and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Coordinate with different functional teams to implement models andmonitoroutcomes.
• Develop processes and tools tomonitorand analyze model performance and data accuracy.

Qualifications:

• Bachelor s degree in engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 8+yearsofexperience inData Sciencefield
• Expertiseusing statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
• Expertisecreating and using advancedmachine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark,Gurobi, MySQL, etc.
• Experience working with and creating data architectures.
• Experience withGenAIapplications.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and masternew technologiesand techniques.
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3,ggplot, etc.