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Key job responsibilities
Key responsibilities include, but are not limited to:
• Support the development of continuously-evolving business analytics and data models, own the quantitative analysis of the performance of our sales team, customers, deal team, partners, markets, and products/services in context of private pricing.
• Use machine learning, data mining, statistical techniques and run A/B experiments to solve complex business problems.
• Perform hand-on analysis and modeling of large datasets to develop actionable insights
• Design, develop and evaluate highly innovative models for predictive learning.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
• Develop a deep understanding of sales metrics, reporting tools, and data structures in order to identify and drive resolution of issues, provide actionable intelligence with existing metrics or identify, develop, and propose new metrics, dashboards, scorecards or new tools.
• Develop relationships and processes with sales, finance, sales operations, and other functional teams to identify and address reporting issues.
• Manage and develop advanced analytical tools that align, and simplify, monthly business reviews, annual planning, and forecasting processes.
• Create operational templates and processes to compile and standardize disparate information that drive standardized reporting and metrics tracking.
• Generate ad-hoc and monthly operational analysis and reports, based on the needs of the stakeholders.
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
- Experience documenting modeling for technical and business leaders
- Experience working with data engineers and business intelligence engineers collaboratively
- Demonstrated expertise in AI/ML, forecasting, predictive models, classification, clustering and other advanced data science applications.
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