Principal Data Scientist

Position Background:   

We are looking for an enthusiastic, experienced ML scientist to join HP’s marketing data science team. In this role, you will have the opportunity to define the scientific approach to a new area of model development, frequently contribute to the development of innovative ideas and methods, coach the less experienced staff members, and leads several complex projects. This person will work to identify business needs, align with key stakeholders, and is passionate about problem solving through power of ML and AI, seamlessly connects model findings to business strategy, and generating recommendations that guide and grow the business.  

Responsibilities:   

• Defines new approaches that could be considered industry wide innovations (next practices)  

• Defines and implements models to uncover patterns and predictions creating business value and innovation  

• Uses their expertise and influence to change the way HP thinks about current business strategy  

• Provides guidance, training and mentoring to less experienced staff members  

• Provides domain-specific expertise in cross-organization projects/initiatives  

• Effectively collaborates with Managers, Directors, EXEC2s and EXEC3  

• Develops clear presentations for senior decision makers including case for change, options, trade-offs and recommendation  

• Manages relationships with business partners to evaluate and foster data driven innovation, provide domain-specific expertise in cross-organization projects/initiatives  

• Supports their people leader with skills assessment, feedback, hiring criteria/approach  

• Ties insights into effective visualizations communicating business value and innovation potential  

• Maintains proficiency within the data science domain by keeping up with technology and trend shifts. Contributes to industry data science domain initiatives  

Job Requirements:  

• Extensive experience using statistics, mathematics, algorithms, and programming languages to solve business problems and deploy ML models into production at scale.  

• Theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc. 

• Advanced proficiency in Python and SQL, comfortable on the command line  

• Ability to effectively communicate data insights to non-technical audiences and at senior management levels