Sr. Decision Science Strategist
United States, San Diego, CA
Applications have closed
PlayStation Global
Erkunde die neue Generation von PlayStation 4- und PS5-Konsolen – erlebe immersives Gaming mit Tausenden Spiele-Hits aus allen Genres, die die Regeln für das, was eine PlayStation-Konsole kann, neu schreiben.Why PlayStation?
PlayStation isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation®5, PlayStation®4, PlayStation®VR, PlayStation®Plus, PlayStation™Now, acclaimed PlayStation software titles from PlayStation Studios, and more.
PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.
The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Corporation.
Sr. Decision Scientist
San Diego, CA (hybrid)
The E-Commerce (D2C) Decision Science team's charter consists of Data Science, Data Engineering, and ML Engineering practices. These teams together are uniquely positioned to be able to provide services across the whole customer experience including the PlayStation Stores and back-end Fraud and Payment systems.
We are looking for a hardworking individual to assist in expediting adoption of data driven solutions provided by this Decision Science teams. This person will need to have deep experience with Decision Science and excellent communication skills to partner with senior business owners across the company. This role will have large impact across the broader organization as key data/data science solutions are deployed redefining existing business practices.
What you'll be doing:
- The candidate will serve as the lead for both immediate team and external partners for Decision Science inquiries.
- Partner with cross-functional teams to define success metrics, build approaches to supervise Decision Science adoption, quantify and evaluate the data, then develop a common language for all colleagues to understand the process.
- Evangelize data knowledge, insights, and value of operating as a data driven organization
- Education support of immediate team as well as external partners on the importance and benefit of using analytics. This should entail proactively sharing results, presenting new solutions as well as demonstrating constant monitoring of current ones.
- Be a SME and Product Owner for various aspects for the Decision Science set of solutions.
What we're looking for:
- Master’s degree in Data Engineering, Statistics, Operations Research, Computer Science or other related fields and a minimum of 7 years’ related work experience.
- 5+ years working with statistical modeling techniques (Regression, CHAID, Neural Networks, Cluster Analysis, RFs, XGBs, etc.) required.
- 5+ years working with data such as querying, storing, automating, programming
Preferred Qualities:
- Recent, hands-on experience working with multiple areas of Decision Science practices
- Proven understanding of predictive modeling, data manipulation, data value assessment, Big Data and BI tools
- Experience illustrating self-sufficiency on sophisticated projects with ability to drive tasks to completion.
- Effective communication skills – being an influencing and occasionally persuasive person
#LI-SV1
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy or maternity, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Tags: Big Data Cluster analysis Computer Science E-commerce Engineering Machine Learning Predictive modeling Research Statistical modeling Statistics VR
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