Data Science is at the core of Nielsen’s business. Our team of researchers come from diverse disciplines and they drive innovation, new product ideation, experimental design and testing, complex analysis and delivery of data insights around the world. We support all International Media clients and are located where our clients are.\n\nLead Data Scientist - Remote - 101791\nData Science - Remote \n\nThe Lead Data Scientist’s primary responsibility in the Audio Data Science team is to develop creative solutions to enhance the data and analysis infrastructure and pipeline which underpins the survey quality for all Nielsen Audio survey products.  In order to deliver high quality standards, the Data Scientist will work as subject matter expert on a team of analysts to establish, maintain and continuously improve data tools and processes supporting the Audio data science team.  \nTasks will include developing system enhancements, procedural and technological documentation, working with cross functional teams to implement solutions into production systems, supporting survey methodology enhancement projects, and supporting client facing data requests.\n\nWhat will I do?\nMaintain and continuously improve the variety of data infrastructure, analysis, production and QA processes for the Audio Data Science team\nAssist in the transition of the data science tech infrastructure away from legacy systems and methods\nWork with cross-functional teams to implement and validate enhanced audience measurement methodologies\nBuild and refine data queries from large relational databases/data warehouses/data lakes for various analyses and/or requests\nUtilize tools such as Python, Tableau, AWS, Databricks etc. to independently develop, test and implement high quality custom, modular code to perform complex data analysis, visualizations, and answer client queries\nMaintain and update comprehensive documentation on departmental procedures, checklists and metrics\nImplement prevention and detection controls to ensure data integrity, as well as detect and address quality escapes\nWork closely with internal customers and IT personnel to improve current processes and engineer new methods, frameworks and data pipelines\nWork as an integral member of the Audio Data Science team in a time-critical production environment\nKey tasks include – but are not limited to – data integration, data harmonization, automation, examining large volumes of data, identifying & implementing methodological, process & technology improvements\nDevelop and maintain the underlying infrastructure to support forecasting & statistical models, machine learning solutions, big data pipelines (from internal and external sources) used in a production environment\n\nIs this for me?\nUndergraduate or graduate degree in mathematics, statistics, engineering, computer science, economics, business or fields that employ rigorous data analysis\nMust be proficient with Python (and Spark/Scala) to develop sharable software with the appropriate technical documentation\nExperience utilizing Gitlab, Git or similar to manage code development\nExperience utilizing Apache Spark, Databricks & Airflow\nExpertize with Tableau, or other data visualization software and techniques\nExperience in containerization such as Docker and/or Kubernetes\nExpertize in querying large datasets with SQL and of working with Oracle, Netezza, Data Warehouse and Data Lake data structures\nExperience in leveraging CI/CD pipelines\nExperience utilizing cloud computing platforms such as AWS, Azure, etc\nStrong ability to proactively gather information, work independently as well as within an multi disciplinary team\nE- Proficiency in MS Office suite (Excel, Access, PowerPoint and Word) and/or Google Office Apps (Sheets, Docs, Slides, Gmail)\n\nPreferred\nKnowledge of machine learning and data modeling techniques such as Time Series, Decision Trees, Random Forests, SVM, Neural Networks, Incremental Response Modeling, and Credit Scoring\nKnowledge of survey sampling methodologies\nKnowledge of statistical tests and procedures such as ANOVA, Chi-squared, Correlation, Regression, etc\n#LI-SF1\n\nABOUT NIELSEN\nAs the arbiter of truth, Nielsen Global Media fuels the media industry with unbiased, reliable data about what people watch and listen to. To discover what’s true, we measure across all channels and platforms⁠—from podcasts to streaming TV to social media. And when companies and advertisers are armed with the truth, they have a deeper understanding of their audiences and can accelerate growth. \nDo you want to move the industry forward with Nielsen? Our people are the driving force. Your thoughts, ideas and expertise can propel us forward. Whether you have fresh thinking around maximizing a new technology or you see a gap in the market, we are here to listen and take action. Our team is made strong by a diversity of thoughts, experiences, skills, and backgrounds. You’ll enjoy working with smart, fun, curious colleagues, who are passionate about their work. Come be part of a team that motivates you to do your best work!  \n\nNielsen is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class.\n\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Data Science, Executive, Cloud, Git, Python, Engineer and Apache jobs that are similar:\n\n $80,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n