Job Information
HP Inc. Data Scientist for Digital Pricing in Tlaquepaque, Mexico
As Data Scientist in the Pricing Analytics team you will shape HP's future of how we set prices. We are a very dynamic, highly skilled and diverse global team consisting of data scientists, economists, statisticians, computer scientists and engineers, who are pushing the innovation frontier in the way HP sets prices for its products. Working with us you will combine your modelling skills, economic/business thinking, experimentation and optimization methods to build complex pricing algorithms for most popular Printers and PCs in the market.
About you:
You have deep interests in customer and market behaviour and methods to measure and anticipate it
You are passionate about unveiling answers to most difficult questions using data and models
You feel accomplished seeing your pricing recommendations being implemented while shopping for yourself
You can't stop thinking about learning something new every day and enjoy being surrounded by highly talented people
Key responsibilities:
Develop and apply data science and statistical methods and experimentation to analyze the effect of pricing and sales decisions on business performance
Prototype pricing algorithms and work with machine learning engineers to efficiently scale algorithms to multi-product and multi-market contexts
Collaborate with internal stakeholders to design and deploy pricing initiatives based upon analytical findings
Present results and recommendations to relevant stakeholders, including senior leadership
Requirements:
Must-haves:
At least 5 years' working experience in data science, including graduate coursework
Master's or PhD degree in Economics, Computer Science, Engineering, Mathematics, Physics or related disciplines
Proficiency with Python or R
Working knowledge of SQL
Theoretical and applied skills in Machine Learning and Statistics/Econometrics
Experience in designing, deploying, and analyzing in-market experiments and/or AB tests
Ability to think creatively and invent original solutions to business and modelling challenges
Ability to build and interpret complex regression models, with machine learning experience a plus
Bonus points for:
Interest in pricing, economics, and consumer behavior
Experience in deploying ML and data science solutions
Experience developing and deploying bandit-style algorithms
Knowledge of discrete choice demand estimation strategies including BLP and mixed logit.
Knowledge of price optimization approaches, price discrimination models and a general knowledge of main concepts from the industrial organization literature
Basic understanding of finance and product economics
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Equal Opportunity Employer (EEO):
HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).