Senior Data Scientist (Audience & Consumer Insights)

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.

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 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!

This role is based out of Mumbai ,is part of GCM team and will be reporting to the Lead Data Scientist.

To build and maintain robust data pipelines that support the advanced analytics needs of Nielsen's audience measurement products (esp NielsenOne)  that provide value for clients.

The role entails ensuring data quality and accessibility, optimizing data flow and storage, and collaborating with data scientists to implement scalable solutions for complex data challenges

Responsibilities

• Design, develop, optimize, and maintain robust data architecture and pipelines, aligning with ETL principles and Nielsen's business objectives.
• Tackle complex data challenges to deliver actionable insights, aiding in the achievement of organizational goals and meaningful client impact.
• 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.
• Develop data products to enhance the productivity of analytics and data science teams solving client problems.
• 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 tools and processes in analytic data engineering, boosting the team's overall efficiency and effectiveness.
• Develop and execute communication and educational plans regarding analytic data engineering capabilities and standards.
• Develop strategies for data storage and retrieval that are efficient and scalable, accommodating the growing data needs of the organization.
• 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.

Key Skills

• Bachelor’s degree required; preferably in Computer Science, MIS, or Engineering.
• At least 2 years in data engineering or a related role, with expertise in SQL, data analysis, and at least one programming language.
• Experience in media/content management/advertising industry is good to have.
• Experience with cloud computing services and infrastructure in the data and analytics space.

Technical Skills

• Advanced skills in SQL and experience in programming languages like Python or Scala.
• Strong background in database development, particularly with Hadoop or BigQuery.
• Experience with big data development tools like Hive, Impala, Spark, and Kafka is beneficial.
• Proficiency in BI tools (Tableau, Power BI, Looker, Shiny).
• Conceptual understanding of ETL, data governance, data warehousing, and cloud-based environments (e.g., Azure, AWS)Self-motivated with a keen problem-solving aptitude and a continuous learning mindset.
• Prioritizes a customer-first approach by anchoring and solving customer problems rapidly, aligning data-driven decisions with customer needs to deliver rapid customer impact.
• Demonstrates a strong work ethic, capable of working abstractly.

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