Lead Data Scientist (Only Chicago - IL)
@ NielsenIQ

Hybrid
Hybrid
Full-time
Posted 11 days ago

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Job Details

About NielsenIQ

NIQ is a global leader in consumer intelligence, delivering insights into the complete consumer journey. As part of a diverse, global team, NIQ offers innovative solutions and flexible work arrangements.

Job Overview

The Lead Data Scientist will design and implement advanced statistical methodologies including sampling, calibration, projection, and panel data modeling to enhance consumer panel products.

Key Responsibilities

  • Advance the statistical rigor of methodologies.
  • Lead development and refinement of panel data models.
  • Collaborate cross-functionally to align methods with product goals.
  • Support production deployment of enhancements and new solutions.
  • Document findings, methodologies, and best practices.

Qualifications

Strong foundation in statistics, proficiency in Python, SQL, and experience with large-scale data analysis. Excellent communication and collaboration skills are essential.

Nice-to-Have Skills

  • Experience with version control systems.
  • Familiarity with cloud computing technologies such as Azure and Linux.
  • Interest in supporting technology teams in production deployment.

Benefits

Flexible working environment, volunteer time off, LinkedIn Learning, Employee Assistance Program (EAP), comprehensive health insurance, parental leave, life insurance, and education support.

Compensation

Anticipated base compensation ranges between $100,000 and $120,000 with potential sales or performance-based bonuses.

Key skills/competency

Statistics, Sampling, Calibration, Projection, Panel Data, Python, SQL, Modeling, Cloud, Deployment

How to Get Hired at NielsenIQ

🎯 Tips for Getting Hired

  • Research NielsenIQ's culture: Study their global consumer intelligence mission and values.
  • Customize your resume: Highlight statistical and technical expertise in Python and SQL.
  • Prepare for technical interviews: Review sampling, calibration, and panel data methods.
  • Showcase collaboration skills: Emphasize cross-functional project experiences.

📝 Interview Preparation Advice

Technical Preparation

Review advanced statistical methods.
Practice Python coding challenges.
Hone SQL query skills.
Study panel data modeling techniques.

Behavioral Questions

Describe teamwork experiences.
Explain conflict resolution examples.
Discuss leadership in projects.
Share cross-functional collaboration examples.

Frequently Asked Questions