Data Analyst (Nutricia + Kate Farms)

The Data Analyst on the Enterprise Data Intelligence team turns data from across North America Medical Nutrition into trusted, actionable insights. In this role, you will partner with Commercial, Supply Chain, Finance, Marketing, Patient Services, and Medical/Regulatory teams to build reporting, analyze performance, and answer business questions that shape decisions. You will help make data accessible, consistent, and easier to use across the organization.

As a key member of our team, you will play an important role in driving our mission forward. The following responsibilities outline the core expectations and contributions for this position:

• →Develop, maintain, and enhance dashboards and reports in tools such as Power BI or Tableau, giving stakeholders clear visibility into sales, demand, patient and channel trends, and operational performance.
• →Analyze large, multi-source datasets, including sales, claims, syndicated, CRM, supply chain, and patient services data, to identify trends, drivers, risks, and opportunities.
• →Translate business questions into clear analytical requirements and communicate findings in concise, non-technical language.
• →Write and optimize SQL queries to extract, transform, and validate data from enterprise data platforms such as Snowflake or Databricks.
• →Partner with data engineers and data stewards to improve data pipelines, data models, and data quality.
• →Perform data validation, reconciliation, and root-cause analysis to improve accuracy and consistency across reports.
• →Support data governance practices, including metric definitions, documentation, data lineage, and a single source of truth for key performance indicators.
• →Handle sensitive data responsibly and follow applicable privacy, security, and compliance requirements.
• →Support ad hoc analysis and executive requests, prioritizing work based on business impact and urgency.
• →Identify opportunities to automate manual reporting and contribute to team documentation, best practices, and continuous improvement.

• This role is primarily performed in a remote office setting and requires the ability to remain in a stationary position (e.g., seated or standing) for extended periods.
• The employee may be required to travel to Danone corporate offices as needed.

The salary range for this position is $76,000-133,000K USD. The exact salary offered will depend on several factors, including the candidate’s relevant experience, geographic location, internal equity, and market conditions. Danone USA additionally offers a performance-based bonus and has a strong benefits package including Medical, Dental, Vision, Prescription Drug Coverage, 401k Plan, Wellness Program, Life Insurance, Tuition Reimbursement, Flexible Time Off, and Paid Parental Bonding Leave, among other benefit plan options. To give our employees flexibility, Danone is a hybrid work environment.

The ideal candidate will bring a combination of education, experience, and skills that enable them to excel in this position. The following qualifications outline what we’re looking for, including both required and preferred criteria:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Business Analytics, Information Systems, or related field/equivalent experience.
• 2–4 years of experience in a data analyst, business intelligence, or analytics role.
• Experience in healthcare, pharmaceutical, medical nutrition, consumer packaged goods, or another regulated industry is preferred.
• Experience with healthcare or commercial data sources, such as claims, syndicated data, CRM, specialty pharmacy, or distributor data, is preferred.

• Strong SQL skills, including joins, window functions, data validation, and query optimization.
• Hands-on experience with a business intelligence or visualization tool such as Power BI or Tableau.
• Experience with cloud data platforms such as Snowflake, Databricks, or a comparable platform.
• Strong analytical and problem-solving skills with close attention to detail.
• Ability to explain complex findings clearly to technical and non-technical audiences.
• Ability to manage multiple priorities and work effectively with cross-functional partners.
• Working knowledge of Python or R for analysis and automation is preferred.
• Understanding data modeling, ETL/ELT concepts, data governance, and advanced Excel is preferred.
• Demonstrates curiosity and ownership, business partnership, collaboration, clear communication, and integrity with data.