Machine learning Engineer
Job Summary
Job Description
Nielsen seeks an organized, detail-oriented Software ML Engineer to join their Audience Measurement Engineering team. The role involves defining, developing, testing, analyzing, and delivering technology solutions within Nielsen's Collections platforms, supporting television viewing measurement across 30+ countries. Responsibilities include working with web technologies (Java, Python, JavaScript, React/Redux, Kotlin), utilizing machine learning frameworks (PyTorch preferred), performing statistical analysis, and working with relational databases and big data (SQL). The ideal candidate possesses strong software development, testing, and debugging skills, along with experience in Git, Jira, and Confluence.
Must have:
- Bachelor's degree in Computer Science or equivalent
- 6+ years software experience
- Experience with ML frameworks and models (PyTorch preferred)
- Strong understanding of statistical analysis
- Proficient in Java, Python, JavaScript, React/Redux, Kotlin
- Experience with SQL and big data
- Proficient with Git, GitFlow, Jira, Gitlab, Confluence
Good to have:
- AWS ecosystem understanding (EC2, S3, EMR, Lambda)
- RESTful API experience
- Experience in test automation
15 skills required
Job Details
At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.
Nielsen is seeking an organized, detail oriented, team player, to join the Engineering team in the role of Software ML Engineer. Nielsen’s Audience Measurement Engineering platforms support the measurement of television viewing in more than 30 countries around the world. The Software Engineer will be responsible to define, develop, test, analyze, and deliver technology solutions within Nielsen’s Collections platforms.
Required skills
- Bachelor's degree in Computer Science or equivalent degree.6+ years of software experience Experience with Machine learning frameworks and models.
- Pytorch experience preferred Strong understanding of statistical analysis and mathematical data manipulation Work with web technology including Java, Python, JavaScript, React/Redux, Kotlin.
- Follow best practices for software development and deployment.
- Understanding of relational database, big data, and experience in SQL.
- Proficient at using GIT, GitFlow, JIRA, Gitlab and Confluence. Strong analytical and problem solving skills.
- Open-minded and passionate to learn and grow technology skills.
- Strong sense of accountability Solution-focused and ability to drive change within the organization.
- Experience in writing unit/integration tests including test automation.
- Strong testing and debugging abilities, functional, analytical and technical abilities, ability to find bugs, attention to detail, troubleshooting
Additional Useful Skills
- A fundamental understanding of the AWS ecosystem (EC2, S3, EMR, Lambda, etc)
- Experienced in building RESTful APIs.
- Experience in writing unit/integration tests including test automation.
Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.
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