AI/ML Freshers Data Scientist

Nielsen's interview process typically begins with a timed online assessment that tests quantitative aptitude, logical reasoning and basic coding. The technical interview dives deep into machine learning fundamentals, Python programming, data manipulation and scenario‑based case studies. The final HR round focuses on cultural fit, communication skills and career aspirations. Candidates should practice end‑to‑end ML projects and be ready to discuss their approach clearly.

Nielsen promotes a data‑driven, collaborative environment where continuous learning is encouraged. Employees benefit from mentorship programs, clear career ladders and a balance between challenging projects and personal well‑being.

Graduates (B.Tech/B.E., B.Sc., M.Tech, M.Sc.) in Data Science, Statistics, Computer Science, Information Technology, Electrical/Electronics or related fields; Minimum aggregate 60% (or CGPA 6.0/10); Batch 2024‑2026; No active backlogs at the time of application; Strong interest in AI/ML and data analytics.

Round 1: Online Assessment (aptitude + coding) → Round 2: Technical Interview (ML concepts, Python coding, case studies) → Round 3: HR Interview (fit, motivation, cultural fit)

Nielsen is a world‑leading data and measurement company that helps brands, media owners and agencies understand audience behaviour across television, digital and audio platforms. With a presence in more than 100 countries, Nielsen combines deep statistical expertise with cutting‑edge technology to deliver insights that drive business decisions. The company’s culture is rooted in curiosity, data‑driven thinking and a collaborative spirit, making it an ideal place for fresh talent to grow. The AI/ML Freshers Data Scientist role in Bengaluru is crafted for candidates who have a strong foundation in data science, machine learning and cloud technologies, yet are eager to gain hands‑on experience on production‑grade projects. As a junior member of the analytics team, you will be exposed to large‑scale audience measurement datasets, end‑to‑end data pipelines, and real‑world model deployment challenges. The position blends responsibilities of a data scientist, software developer and data engineer, offering a holistic view of the data product lifecycle. Key Responsibilities: 1. Design, develop and maintain scalable data pipelines using Apache Spark and AWS services. 2. Conduct exploratory data analysis to uncover patterns in media consumption data. 3. Build, train and evaluate machine learning models for audience measurement, bias reduction and missing‑data imputation. 4. Write clean, modular Python code and integrate models into production APIs. 5. Collaborate with senior data scientists and engineers to translate business requirements into technical solutions. 6. Create dashboards and visualisations using Tableau or Spotfire to communicate insights to stakeholders. 7. Perform statistical testing and validation to ensure model robustness. 8. Document code, workflows and findings in Confluence for knowledge sharing. 9. Participate in code reviews and adopt best practices using Git and GitLab. 10. Stay updated with emerging AI/ML techniques and propose innovative solutions. Tech Stack: Python, SQL, Apache Spark, AWS (S3, EC2, Lambda), Machine Learning libraries (scikit‑learn, TensorFlow/PyTorch), Git, GitLab, JIRA, Confluence, Tableau/Spotfire. Growth Path: Starting as an AI/ML Data Scientist I, you can progress to senior data scientist, machine learning engineer, AI engineer, data engineer, analytics engineer, and eventually lead data science or AI/ML research roles, depending on your interests and performance. Why Join Nielsen? You will work on high‑impact projects that shape media strategies for global brands, gain exposure to massive real‑world datasets, and develop end‑to‑end AI/ML solutions in a supportive, learning‑centric environment. The hybrid work model offers flexibility while fostering collaboration with cross‑functional teams across the globe.