Job Description

Job Summary Nielsen is a leading online, radio and television research company specializing in industry leading measurement solutions that provide clients with a comprehensive understanding of the online world. Our Data Science team is experimenting, testing, and driving major insights that impact both a global network of clients and our own Nielsen direction. As a Data Scientist you will be responsible for high-quality design, execution and delivery of global analytics solutions, performance dashboards, and analytical studies. Excited? Come join us! The Advanced Audience Team focuses on methodologies and pipelines that measure how effectively these campaigns reach targeted audiences, as defined by the client, or via demographics, or even pre-defined audiences from our partners. The team builds and maintains robust data pipelines that support the advanced analytics needs of Nielsens audience measurement products that provide value for clients. The role entails ensuring data quality and accessibility, optimizing data flow and storage, and collaborating with other data scientists to implement scalable solutions for complex data challenges Responsibilities Design, develop, optimize, and maintain robust data architecture, methodologies, and pipelines, aligning with ETL principles and Nielsens business objectives. Tackle complex data challenges to deliver actionable insights, aiding in the achievement of organizational goals and meaningful client impact. Develop data science methodologies and solutions that solve key client problems, and that are reproducible and scalable. Ensure the integration of disparate data sources into a cohesive and efficient data ecosystem, facilitating seamless data accessibility and interoperability for various analytical platforms and stakeholders throughout Nielsen. Offer mentorship, advice, and coaching to other professionals in data and analytics on best practices and standards. Lead in the evaluation and deployment of cutting-edge methodologies and processes in data science, boosting the teams overall efficiency and effectiveness. Collaborate with business analysts and solutions architects to devise technical architectures for key enterprise projects and initiatives that improve client experience. Engage in continuous learning in areas like machine learning, data science, AI, statistics, and applied mathematics Skills Masters degree in Data Science, Computer Science, Statistics or Mathematics, Operation Research, or other hard sciences) with outstanding analytical expertise and strong technical leadership skills. Proficient in Python or other general purpose programming languages, or other statistical/data processing packages. Have a thirst for new challenges. The candidate should be comfortable diving into the unknown and making sense of whats noise and what isnt. Have an eye for design at multiple levels: Infrastructure architecture (cloud infrastructure), ETL data pipelines, and analytic pipelines. Have Experience building analytic methodologies: either from scratch, using existing software libraries and APls, and/or combinations of the two. Feel comfortable and excited to bring innovative ideas and challenge existing methods and processes. This requires the ability to pick apart the implementation details from the overall design. Have a mathematical and/or statistical background with the ability to dive "into-the-weeds" when necessary to help fine-tune methods and models. Help incubate a forward-thinking culture in a growing data-science organization. This includes prioritizing staying up-to-date with new software, methodologies, and industry research and facilitating the cross pollination of ideas across individuals and teams. Be self-motivated with a keen problem-solving aptitude and a continuous learning mindset. Demonstrates a strong work ethic, capable of working abstractly. Be able to communicate effectively to various types of personas: commercial partners, product leaders, infrastructure architects, data scientists, and data engineers. 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 youre unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.