Data & Analytics Specialist

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Data & Analytics Specialist 

Purpose:

The Data & Analytics Specialist is a hands-on operational role responsible for supporting the reliable, accurate, and timely flow of data that powers business decisions, commercial intelligence, and AI enablement. The role focuses on the execution of data quality tasks, vendor feed monitoring, reporting support, business rule maintenance, and process documentation — contributing to the team's ability to deliver trusted, activation-ready data at scale.

This role represents the evolving business data analyst — moving beyond static reporting toward ensuring data flows, quality, and structure are robust enough to support both human decision-making and AI-driven intelligence. The specialist supports hands-on data work (analytics requests, business rule updates, issue resolution, vendor feed coordination) while building capability in making data AI-ready and leveraging AI tools in daily operations. They develop business context — learning what the data means commercially — while building the technical fluency to work across platforms, taxonomies, and data pipelines.

This is not a traditional reporting role. It is a role for someone who recognizes that the value chain of data is shifting — from "pull a report" to "ensure the machine can interpret, validate, and surface insight autonomously." The specialist supports ensuring data is structured, documented, governed, and contextually enriched so that both BI dashboards and AI products deliver trusted, actionable outputs. They are developing the ability to move fluidly between resolving a data quality issue, monitoring a vendor delivery, supporting a Power BI report, or preparing data for an AI model — and they are building the business understanding to know why each task matters commercially.

This role operates with an AI-aware mindset. Tasks — from data validation to documentation — are executed with growing awareness of how they enable or constrain AI tools downstream. The specialist learns that clean, well-structured, semantically rich data is the fuel for AI-powered products and begins to shape their own work to maximize AI readiness. This means developing the habit of thinking beyond "is this data correct?" toward "can a machine interpret this data accurately and consistently?"

As organizations transition from manual, request-driven analytics to self-service, AI-augmented intelligence, this role contributes to the operational backbone that makes that transition possible — supporting data feeds, taxonomy updates, remediation workflows, and AI-ready datasets under the guidance of senior team members.

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Scope (global, regional or local):

Global /Local

Key Tasks/ What You'll Do

• Support the coordination and monitoring of data deliveries from self-service analytics (SSA) platforms and external vendors — checking timeliness, completeness, and format compliance — and escalating gaps, anomalies, or issues to senior team members.
• Maintain and update business rules, mapping logic, taxonomies, and classification standards under guidance — ensuring they reflect current market realities and are structured for both human and machine consumption.
• Investigate and help resolve data quality issues — supporting root cause analysis, implementing corrective actions, and documenting resolutions for future prevention.
• Support analytics and BI reporting requests — preparing data, validating outputs, assisting with Power BI dashboard maintenance, and ensuring reports reflect accurate and timely information.
• Assist with local market data requests and ad-hoc analytical needs — acting as a supporting link between market teams, global data platforms, and cross-functional stakeholders.
• Flag opportunities to transition recurring manual requests into self-service reporting or automated delivery.
• Prepare and structure data for AI use cases — ensuring datasets are clean, well-labeled, and documented with the context AI models need to interpret them accurately, with growing consideration for how attributes will be consumed by AI models.
• Support the operationalization of AI products — assisting with data validation, output testing, and feedback loops under the direction of senior specialists.
• Use AI tools (e.g., Copilot, GenAI assistants, n8n, automation scripts) in daily work to increase efficiency and reduce manual effort — developing fluency in AI-augmented operations.
• Identify potential automation opportunities within data operations — flagging where AI or rule-based automation could replace repetitive manual tasks in mapping, validation, and quality checks.
• Create and maintain operational documentation — including process SOPs, mapping logic, vendor feed specifications, and troubleshooting guides — written with clarity and structure that supports both human users and AI system context layers.
• Support onboarding of new team members and contribute to continuous improvement by flagging recurring issues and suggesting process enhancements.

Key Working Relation:

• Global / Local Team
• Local/Regional Business Teams & Stakeholders
• IT / Data Engineering & Data Science teams
• External Data Providers (e.g., IQVIA, NielsenIQ, GfK, Euromonitor)
• Commercial Analytics & BI users
• AI / Digital Innovation teams

Qualification & Competencies:

• Bachelor's degree in Business, Economics, Data Analytics, Information Management, or related field.
• 1–3 years of experience in data operations, data quality, business analytics support, or commercial data analytics — experience in FMCG, Consumer Health, or Pharmaceuticals is a plus but not required.
• Some exposure to syndicated market data (IQVIA, NielsenIQ, GfK) or willingness to learn — including familiarity with data structures, delivery formats, and common quality issues.
• Basic experience or understanding of data mapping rules, product matching logic, and classification standards.
• Good analytical and problem-solving skills — ability to investigate data issues methodically and support resolution.
• Proficiency in Excel (advanced formulas, pivot tables, data manipulation); good knowledge of SQL, Power BI, or similar tools is a plus.
• Strong personal drive to explore, test, and use AI tools, systems, and automation approaches in daily work — with a proactive habit of experimenting and learning.
• Interest in automation concepts (e.g., scripting basics, workflow tools, AI-assisted data processes, prompt engineering fundamentals).
• Detail-oriented with good organizational skills and ability to manage multiple tasks with appropriate prioritization.
• Ability to create clear process documentation and follow established SOPs.
• Good communicator — able to work across cultures and functions, explain data issues clearly to colleagues and stakeholders.
• Self-motivated, reliable, and comfortable working in a global, matrixed environment with remote collaboration.
• Growth mindset — views AI as a learning opportunity and actively seeks to integrate AI into personal workflows.
• Fluent English required; additional languages a plus.

Location:

Spain : Cataluña : Barcelona  

Division:

Enabling Functions 

Reference Code:

875473