Senior Data Scientist (Python, SQL, Spark)

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.