Nielsen AI ML data scientist I recruitment 2026, Bengaluru

Nielsen off campus hiring is open in Bengaluru for an AI / ML Data Scientist I, and it is a strong early-career role for anyone who wants to work at the meeting point of data science, machine learning and software engineering. Nielsen is the global leader in measuring what people watch and listen to across TV, digital and audio, and data science sits at the heart of that mission. The role accepts 0 to 3 years of experience, so genuine freshers with the right skills can apply.

This post pulls together everything you need: what the role involves, who can apply, the exact tools and skills Nielsen lists, how to prepare, a realistic view of the selection process, and answers to common questions. Apply only through the official Nielsen careers link on this page.

About Nielsen

Nielsen Media is the global leader in audience measurement, helping publishers, advertisers and agencies understand what people watch and listen to as the media industry keeps changing. Its data science team includes computer scientists, statisticians, data scientists and behavioural methodologists, and it works on methodology and software development together. For an early-career data scientist, that mix is a rare chance to learn both the science and the engineering side of real, large-scale measurement work.

About this role at Nielsen

As an AI / ML Data Scientist I you bridge data science, sampling analytics, software development and data engineering. Nielsen is clear that the ideal candidate is equally excited about building models at scale and writing production-ready software that can run in the cloud. You will understand machine learning, apply good software development practices across a team, and stay curious enough to keep learning from your peers. It is a hands-on role where your models and code actually go into production.

Key responsibilities

Based on the official listing, your work spans building solutions, deploying them and researching methodology. You can expect to:

• Build measurement and planning solutions for publishers, advertisers and agencies
• Identify AI opportunities in existing and new projects and implement them
• Support reproducible data science projects end to end
• Deploy and maintain data pipelines and models in a production environment
• Work with cross-functional teams to productionise, validate and optimise methodologies
• Communicate methodology and research findings clearly to different audiences
• Explore data through variable identification, cleaning, dimension reduction and integration, and check accuracy with output-evaluation techniques
• Address quality issues and fix problems in production code, and document new methodologies

Eligibility and who can apply

The experience band is fresher-friendly, and the eligible degrees are broad across quantitative fields, which makes this a genuine option for early-career candidates.

• 0 to 3 years of work experience (so freshers can apply)
• A degree in data science, statistics, engineering, applied mathematics, operations research, information sciences or another biological or physical science
• Proficiency in Python, Spark, AWS and SQL, with a foundation in artificial intelligence and machine learning
• The ability to manipulate, analyse and interpret large datasets
• Excellent oral and written communication and strong interpersonal skills

Tools and skills Nielsen looks for

This is a hands-on, production-focused role, so the tools matter. Make sure your resume reflects the ones you genuinely know, and build the others while you prepare:

• Python for modelling and production code, plus SQL for working with data
• Spark for large-scale data processing and AWS or Google Cloud for cloud computing
• A working knowledge of statistics and machine learning
• Strong code documentation habits and proficiency with Git and GitLab
• Familiarity with the Atlassian suite such as JIRA and Confluence
• Dashboarding and visualisation tools such as Spotfire or Tableau

What you will work on and your growth path

The research areas here are genuinely interesting for a data scientist: trend analysis, imputing missing data, representation and sampling, bias reduction, indirect estimation, data integration and automation. You get to move between exploring messy data, building models and shipping production software, which is exactly the range of skills that makes early-career data scientists grow fast. Because Nielsen pairs methodology with software development, you learn to write code that others can rely on, not just notebooks that run once.

Why this is a strong early-career move

For a first or early data science job, the mix Nielsen offers is hard to beat. You work on measurement that real publishers, advertisers and agencies depend on, so your models have visible impact rather than sitting in a report nobody reads. You also learn to ship production software, which is the skill that separates data scientists who stay in notebooks from those who grow quickly. Working alongside statisticians, computer scientists and methodologists means you pick up both the maths and the engineering, and that combination compounds fast in the first few years of a career.

The research topics are genuinely meaty too. Trend analysis, missing-data imputation, sampling and representation, bias reduction and data integration are the kinds of problems that teach you to think carefully about data quality, not just model accuracy. If you want a role where you keep learning and your work is used, this is a good one to aim for, and the tools you pick up here, from Python and Spark to cloud platforms and production machine learning, transfer directly to almost any data or AI role you take next.

Salary and what to expect

The listing does not publish a salary, so confirm the numbers during the official process and ignore any specific figure on unofficial pages. What you can expect is a fast-paced environment, real production work and a team of experienced scientists and engineers to learn from, which is a strong foundation for an AI and machine learning career.

Selection process and what to expect

A typical selection process for an early-career data science role like this moves through an online application, a resume and skills screen, one or more technical rounds covering Python, SQL, statistics and machine learning, and a discussion of a past project or case. Be ready to explain how you cleaned data, chose a model and checked its accuracy. Confirm the exact stages on the official Nielsen page.

How to apply for Nielsen off campus 2026

Apply only through the official Nielsen careers portal linked on this page. Nielsen itself warns that job-seekers can be targeted by scammers, and it confirms that its recruiters only contact candidates through official job boards, LinkedIn or an email ending in nielsen.com. Never pay anyone for a job, and always verify that any communication comes from an official Nielsen address.

How to prepare before you apply

Focus your preparation on the practical side of data science. Be comfortable writing Python and SQL, and be able to talk through a project where you cleaned data, built a model and measured how well it worked. Brush up on the basics of statistics and machine learning, and get comfortable explaining your thinking simply, since clear communication is called out in the listing.

• Practise Python and SQL on real datasets, not just tutorials
• Revise core statistics and machine-learning concepts
• Prepare one end-to-end project you can explain: data, model, evaluation
• Get familiar with Git, and ideally a cloud free tier and Spark basics
• Be ready to explain your results clearly to a non-technical listener

Resume tips for this role

• Lead with your degree, graduation year and quantitative subjects
• List Python, SQL, ML libraries and any cloud tools you actually use
• Describe projects with the dataset, the method and the measurable result
• Add your GitHub or portfolio link so reviewers can see your code
• Keep it to one clean, ATS-friendly page

Frequently asked questions

Can freshers apply for this role?

Yes. The listing asks for 0 to 3 years of experience, so freshers with the right skills in Python, SQL and machine learning can apply.

Which degrees are eligible?

A degree in data science, statistics, engineering, applied mathematics, operations research, information sciences or another biological or physical science.

What tools should I know?

Python, SQL, Spark and AWS are core, along with a foundation in machine learning. Git, JIRA, Confluence and a visualisation tool like Tableau or Spotfire are valued too.

Where is the job located?

Bengaluru, India. Confirm the work location and work mode on the official Nielsen page.

Is this a coding role or a research role?

It is both. Nielsen is clear that you build models at scale and write production-ready software that runs in the cloud, and you also support methodology research such as sampling, bias reduction and data integration. That blend of engineering and science is what makes it a strong early-career data science role.

How do I avoid job scams?

Nielsen recruiters only contact candidates through official job boards, LinkedIn or an email ending in nielsen.com. Never pay for a job, and verify any message against Nielsen's official website.

A quick, honest note

Confirm the role, the location and the eligibility on the official Nielsen page before you apply, and keep your application confirmation safe. ClassicJobs only points you to the official listing and never charges a rupee.