{"id":2619302,"url":"https://alion.io/job/nielsen-ai-ml-data-scientist-ii-2","title":"AI / ML Data Scientist II","company":{"id":837,"name":"Nielsen","domain":"nielsen.com","url":"https://alion.io/company/nielsen","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":20,"computed_at":"2026-10-28T05:59:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":32},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-15T12:30:29Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-28T21:10:51Z","board_verified":true,"closed_at":null,"days_open":13,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":13},"description":"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.\n About the Role\nThis job description outlines the responsibilities and qualifications for an AI / ML Data Scientist II role with a primary focus on designing, building, and deploying scalable machine learning systems, software engineering best practices, and the application of AI/ML principles within Machine Learning and Data Science contexts.\nAudience is everything! Nielsen offers the world's most complete measurement of media-viewing behavior. Our data scientists and ML engineers leverage the best data assets and modeling methods to build consistent and comparable metrics of the media landscape in multiple countries. We help the world's biggest brands make better and faster media and marketing decisions.\n Responsibilities\nImplement, test, and optimize econometric, statistical, and Machine Learning (ML) models to enhance data accuracy and reporting.\nIdentified the AI opportunities in existing and new projects and implemented them.\nQuickly learn and become an expert in Audience Measurement and the associated digital meter technology for data collection.\nDesign comprehensive ML workflows, develop reliable data pipelines (using Databricks/AWS S3), execute sophisticated model training and evaluation, and clearly summarize results.\nIdentify, integrate, clean, and transform data from disparate and complex data sources to ensure high-quality inputs for ML models.\nDevelop, share, and maintain efficient, well-documented, production-quality code following software engineering best practices.\nProactively incorporate quality checks throughout the ML development lifecycle to detect and correct errors swiftly.\nCreate simple, meaningful visualizations (e.g., using Tableau) to effectively support data analysis and clearly communicate insights and findings to stakeholders.\nTranslate complex research findings into clear, data-driven recommendations that address business needs and drive product/technology improvements.\nPartner closely with department stakeholders (Engineering, Data Science, Product, Technology) to manage timelines, share data, execute tests, and present results.\n Key Skills & Qualifications\nBachelor’s Degree or higher in Mathematics, Statistics, Computer Science, Data Science, Data Engineering, or a closely related quantitative field.\n3-6 years of professional experience in a Data Engineer or similar quantitative role.\nProven ability to manipulate, analyze, and interpret complex data sources to effectively \"tell a story from data\" through impactful analyses.\nProficiency in Python, PySpark, SQL, Artificial intelligence and Machine learning\nDeep understanding and application of Statistics, including hypothesis testing, regression analysis, and experimental design.\nExperience with trending and visualizing data using tools like Tableau\nFamiliarity with Media Data Lake (MDL) concepts is a plus.\nBusiness Skills:\nExcellent oral and written communication\nSelf-motivation and an ability to handle multiple competing priorities in a fast-paced environment\nStrong interpersonal skills and the ability to develop effective relationships with other team members, including remotely.\nPlease 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. 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