NielsenIQ
Market Research
ML/DataAnalyst
Neural analysis suggests this role is
optimal for mid candidates.
“ML / Data Analyst at NielsenIQ. Skills: Data Science, Machine Learning, Business Intelligence, Data Engineering. Develop and implement data models. Build and maintain data pipelines”
Industry & Context.
Analytical skills
What They're Looking For.
Must Have
Bachelor's degree in Statistics, Computer Science, Mathematics, or related field, 3+ years of experience in data analysis or data science, Proficiency in SQL, Experience with Python or R for data analysis
Nice to Have
Master's degree or PhD in a quantitative field, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), Experience with BI tools (Tableau, Power BI), Experience with data warehousing solutions (Snowflake, BigQuery, Redshift), Experience with MLOps practices
What You'll Do.
Develop and implement data models
Build and maintain data pipelines
Perform statistical analysis
Develop machine learning models
Create dashboards and reports
Collaborate with stakeholders
Ensure data quality and integrity
Stay updated on industry trends
How You'll Work.
Team & Collaboration
Cross-functional teams; Business stakeholders
Full Job Description
NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the twoindustry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. Within the Operations team, ML / Data Analyst is responsible for the quality and enhancement of the data that we deliver to external clients. The role ensures that client data is distributed according to contractual agreements and quality standards, while also supporting internal teams and systems involved in the reporting process. Key Responsibilities: Data Quality & Operational Excellence * Proactively monitor and investigate data quality issues, handling complex cases independently. * Implement and validate data enhancements, fixes using SQL, Regex, and internal tools. * Take ownership of the weekly quality check processes, ensuring data deliveries are consistently accurate and on time. Data Processing & Analysis * Perform ML model retraining, monitoring and analyzing performances, and bring enhancements. * Investigate and resolve complex or ambiguous data classification and branding issues. * Efficiency in handling daily, high-volume operational tasks. Collaboration & Communication * Actively work with your team member by sharing information, support each * other and build a cohesive team environment. * Proactively update your manager in Paris on task status, potential risks, or blockers before they become major issues. * Serve as a reliable and solutions-oriented contact point for internal departments, handling operational issues through to resolution. * Contribute to operational process improvements. Compliance & Best Practices * Follow and adhere to all global processes and team best practices. * Maintain strict confidentia
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