Machine Learning Engineer

Job Description

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, and many more! In doing so, the ability to extract information from data and drive action that help achieve business goals is essential. GPFD's data science team is responsible for evaluating online user activity data for potential fraud and revenue optimization across this platform, and the engineering team empowers them. We are looking for a Machine Learning Engineer with experience in productionizing machine learning models to join our GPFD engineering team to support this data science platform.

What you'll be doing:
• Build and enhance machine learning pipelines supporting development, experimentation, continuous integration/delivery, and monitoring of ML models.
• Analyze large data sets using methods like hypothesis testing and experimental design.
• Develop, optimize, and deploy machine learning algorithms and predictive models to solve complex business problems, particularly in fraud detection and payment optimization.
• Conduct robust statistical analysis on big data using various techniques such as hypothesis testing, design of experiments, and inferential statistics.
• Create and maintain cloud-based solutions using AWS services for data streaming, processing, and storage.
• Improve decision performance by analysing misclassification cases, hit rates, and customer feedback.
• Collaborate with multi-functional teams to understand business challenges and recommend data-driven solutions.
• Ensure high levels of service availability and implement automated, repeatable deployment processes.

What we're looking for:
• Master's degree in Computer Science, Machine Learning, or related field; or Bachelor's degree with equivalent work experience,
• Proven track record (3+ years) of implementing end-to-end data science solutions, from data processing to model deployment,
• Strong programming proficiency in Python or Java,
• Demonstrated expertise in working with large-scale SQL analytics databases,
• Experience with cloud services and architectures, such as AWS services,
• Strong communication abilities to work with cross functional teams.

Desirable skills:
• Understanding of adversarial predictive modeling techniques, data manipulation, unstructured data processing, and data value assessment,
• Knowledge of fraud and other ecommerce risks,
• Commitment to continuous learning and staying up-to-date with the latest developments in machine learning, data science, and cloud technologies.

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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, maternity or parental status, 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.

PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Jobcode: Reference SBJ-dyzkzm-52-14-25-246-42 in your application.