Role overview:

Interested in working on strategic initiatives that allow for creativity and room for growth? Do you have strong passion for using data and cutting-edge technologies to drive the best business decisions? If so, read on…

Sony Interactive Entertainment’s (SIE) Global Fraud Management and Global Payment (GPFM) Teams are the guardians of both customer trust and purchase success for PlayStation and the PlayStation® Network (PSN). We provide innovative solutions to support every element of the network, various platform services, customer service teams, a diverse developer community, and more.

We recently launched a next generation risk platform and machine learning framework that support the global, fast-growing PlayStation® Network customer base, world class PlayStation® consoles, hand-held devices, PlayStation® TV, and many more! In doing so, the ability to extract information from data and drive action that help achieve business goals is essential. GPFM’s Data Science team is responsible for evaluating online user activity data for potential fraud across this new platform. Our job is to provide quantitative assessments of all customers and identify those individuals who pose the most risk to our businesses.

What you'll be doing:

• Utilise various approaches to maximise value from predictive analytics solutions.
• Optimise use of developed Machine-Learning algorithms in conjunction with other aspects of decision logic (rules, other models, etc.)
• Demonstrate understanding of predictive modelling methodology that detect fraud and other ecommerce risks.
• Provide feedback to modellers on new features, algos, strategy, and modelling ideas.
• Conduct robust statistical analysis to big data using hypothesis testing, design of experiment, inferential statistics, and more.
• Improve decision performance by analysing misclassification cases, hit rates, and customer feedback.
• Coordinate, document and simplify rule assessment.
• Develop deep understanding of business challenges and recommend data features and functionality that can contribute to identifying risk and possible fraud.
• Assist the Software Development and Peer team members in testing and deploying decision changes (rules, models, etc.) on the newly created platform.

What we're looking for:

• Master’s degree in Statistics, Operations Research, Machine Learning, Computer Science or other related fields
• 2+ years working with statistical modelling techniques (Classification, Regression, CHAID, Neural Networks, Cluster Analysis, RFs, XGBs, etc.).
• Hands-on statistical analysis experience with some understanding of a statistical programming package such as R/Python/Java/other is required, and some visualization applications using Tableau/R Shiny/Python Dash.
• Experience performing large scale data manipulation to assess, clean, merge, and analyses large data sets from different data warehouse sources (Hive, Hadoop, MySQL, SQL, Snowflake, etc.).
• A passion for analysing highly complex data sets, an entrepreneurial spirit, a relentless customer-focus, a practical understanding of quantitative methods, and superb attention to detail.

Desirable skills:

• Demonstrable experience working with Optimisation, statistical analysis, machine learning or text classification algorithms.
• Solid understanding of predictive modelling, data manipulation, unstructured data processing, and data value assessment.
• Creation and understanding of macros for automating above mentioned processes is strongly preferred!

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