Senior Principal Data Scientist, Go-To-Market Strategy & Incentives

The Red Hat Global Sales Go-To-Market Strategy & Incentives team is looking for an experienced Senior Principal Data Scientist to join our team. In this role you will apply your advanced analytic and data science skills to deliver insights that support go-to-market strategy development, which in turn positively impacts Red Hat’s revenue generating programs and projects. You will use data to drive growth, enable high quality and more precise business decisions. This is to enable high quality data to manage the Sales Cadence, and end-to-end Quota Process Transformation, including seller profile, sales roles & measurements module. You will leverage your mathematical and statistical expertise, along with your natural curiosity and creativity, to mine and interpret data to address questions, connect the dots and uncover hidden opportunities to realize the data’s full potential, slicing and dicing it to create new visions for the business. You must be bright and motivated with a balance of technical skills, business savvy, and strong interpersonal and communication skills to help build the next generation of data-driven action and decision making.

What you will do:

• Designs and develops enterprise-class, advanced analytics models to understand and solve complex GTM business problems such as segmentation, quota modeling, resource deployment model creation and Cost of Sales/Sales Productivity.

• Identifies relevant data sources and sets to mine for customer/business opportunities, collecting large structured and unstructured datasets and variables.

• Leads the design, execution and interpretation of data/analytic studies, including algorithm development, sample size calculations, statistical method selection, model development/tuning, etc.

• Transform & improve data quality for all dimensions of Sales management & planning. 

• Create data architecture aligned to the business requirements for Sales Management

• Curate data fit for purpose for end-to-end Incentives process, including target planning, quotas, development & territory structures

• Transform the end-to-end process for Quotas from client segmentation to target setting models for Quotas, Territory & Quota deployment at scale

• Develops processes utilized to perform data and error analysis to improve data modeling; ensures data is clean and validated for uniformity and accuracy to support consistent, meaningful reporting

• Analyzes data for trends and patterns and interpret data with clear objectives in mind.

• Collaboratively develops predictive and advanced intelligence to empower and optimize customer engagements at scale.

• Works closely with key leaders/teams across Sales, Finance, Operations, Marketing and IT, to understand business needs, empower business stakeholders to execute.

• Translates complex analytical and technical concepts to business stakeholders and executive leadership to enable understanding and guide informed business decision making.

• Serves as a lead, overseeing the work of other Data Analysts on the team, serving as a SME across different functional aspects of the work this team undertakes.

• Leverage judgment and interpretative understanding of the data to help resolve critical issues that will have an impact on the long term success of the business.

• Apply learnings from the data, alongside proven theories and concepts, to advise Red Hat executives on proposed strategies and strategy adjustments

What you will bring:

• 15+ years experience manipulating data sets and building statistical models.

• Experience working in or directly with Sales teams in a software/technology company.

• Advanced experience in pattern recognition and predictive modeling.

• Familiarity with business value and use cases of data science concepts such as artificial intelligence and machine learning.

• Knowledge of advanced statistical techniques and concepts (regression, simulation, scenario analysis, clustering, decision trees, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

• Ability to take initiative, manage multiple projects and problem solve in ambiguous situations.

• Excellent written and verbal communication skills, for use in information gathering, presenting findings and coordinating across teams.

• A drive to learn and master new techn