Omnichannel Marketing Data Analyst

Bracco Diagnostics Inc. is a subsidiary of Bracco Imaging which is part of the overall Bracco Group. The Company specializes in the clinical development, marketing and sales of diagnostic contrast imaging agents. Bracco Diagnostics Inc. primarily markets its products to hospitals throughout the United States. Bracco Diagnostics Inc. is committed to the discovery, development, manufacturing and marketing of imaging agents and solutions aimed at providing a better use and management in terms of diagnostic efficacy, patient safety and cost effectiveness.

Please note:

Bracco Diagnostics Inc. is unable to provide sponsorship work authorization status (e.g., H-1B visa status, CPT, OPT or employment-based Green Card).

Hybrid working arrangement working Tuesday, Wednesday and Thursday in-person in the Princeton, New Jersey headquarters is required.

Bracco Diagnostics Inc. is unable to provide relocation assistance for this role.

The Commercial Data & Insights Analyst leads the identification, development, and delivery of data driven insights and process improvement solutions. In this role, the individual will partner closely with regional and global business and technical teams to refine analytical pipelines, validate outputs, and translate complex data into actionable insights.

This role supports key commercial use cases, including omnichannel effectiveness, sales performance, customer engagement, and Next Best Action analytics. The analyst is expected to grow into an increasingly independent contributor, supporting analytics delivery, engaging stakeholders, and helping establish best practices as the function matures.

• Work on analytics that directly support commercial strategy and omnichannel execution
• Collaborate with cross-functional partners in a modern data environment
• Deliver insights that move beyond reporting to measurable business impact
• Join a team that values clarity, rigor, continuous learning, and practical, decision-ready analytics

• Extract, clean, and structure data from multiple sources, including CRM systems, Databricks, and internal data pipelines.
• Use SQL to answer business questions, investigate data discrepancies, validate outputs, and support business stakeholders
• Support Next Best Action (NBA) analytics, including feature analysis, performance monitoring, recommendation uptake, and outcome measurement
• Validate NBA outputs, monitor data drift, and ensure recommendations align with business and clinical context
• Conduct quantitative analyses to identify trends, patterns, and opportunities for improvement across commercial datasets
• Build, maintain, and enhance dashboards and recurring reports to track KPIs and business performance across channels
• Analyze performance across multiple channels (e.g., field, digital, marketing) to support omnichannel measurement and optimization
• Collaborate with data engineers and business stakeholders to ensure analytical outputs align with business needs and priorities
• Document analytical workflows, assumptions, and methodologies to support reproducibility, data quality, and scalability
• Prepare and present stakeholder-ready materials, including dashboards, reports, and summaries that clearly communicate insights and recommendations to non-technical audiences
• Manage analytics projects with increasing independence, from problem definition through analysis, recommendations, and stakeholder communication

• Bachelor’s or Master’s degree in Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field

• 3-5 years of experience in data analysis, business analytics, commercial analytics, data science, or a related role
• Demonstrated experience using SQL and Databricks to answer business questions, investigate data issues, validate outputs, and support business stakeholders in cloud-based analytics environments such as Databricks
• Hands-on Python experience for data manipulation, analysis, and automation
• Experience in commercial, customer, or omnichannel analytics is a strong plus
• Experience with Machine Learning pipelines or model validation practices (e.g., output validation, parameter tuning, model drift monitoring) is preferred

• Strong SQL proficiency is required. Candidates must be able to read, write, and troubleshoot SQL queries for data extraction, transformation, analysis, and validation,…