Senior Data & Analytics Specialist

The Senior Data & Analytics Specialist is a versatile, execution-oriented role that sits at the intersection of data operations, business intelligence, and AI. This is the future of the business data analyst/steward - less about building static reports, more about ensuring data flows, quality, and structure are robust enough to power both human decision-making and AI-driven intelligence at scale.

This role combines hands-on data work (supporting analytics requests, maintaining business rules, troubleshooting issues, coordinating vendor feeds) with a forward-looking mandate to make data AI-ready, leverage AI tools in daily operations, and support the operationalization of AI use cases. The specialist brings critical business context - understanding what the data means commercially - while operating with 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 understands 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 ensures data is structured, documented, governed, and contextually enriched so that both BI dashboards and AI products deliver trusted, actionable outputs. They are equally comfortable resolving a data quality issue, coordinating a vendor delivery, enabling a Power BI report, or preparing data for an AI model - and they bring the business understanding to know why each task matters commercially.

Critically, this role operates with an AI-first mindset. Every task - from data validation to mapping rule definition to documentation - is executed with awareness of how it enables or constrains AI tools downstream. The specialist understands that clean, well-structured, semantically rich data is the fuel for AI-powered products, and actively shapes their own work to maximize AI readiness. This means thinking beyond “is this data correct?” to “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 is the operational backbone that makes that transition possible - one data feed, one taxonomy update, one remediation workflow, and one AI-ready dataset at a time.

Scope (global, regional or local):

Global

Key Tasks/ What You’ll Do

• Coordinate and manage data deliveries from self-service analytics (SSA) platforms and external vendors - ensuring timeliness, completeness, and format compliance - while monitoring feeds proactively to identify gaps, anomalies, or drift before downstream impact.
• Maintain and update business rules, mapping logic, taxonomies, and classification standards - ensuring they reflect current market realities and are structured for both human and machine consumption.
• Troubleshoot data issues end-to-end - from detection through root cause analysis to corrective action - driving remediation with urgency and documenting resolutions for future prevention.
• Support analytics and BI reporting requests - preparing data, validating outputs, maintaining Power BI dashboards, and ensuring reports reflect accurate, timely, and contextually correct information with appropriate business interpretation.
• Facilitate local market data requests and ad-hoc analytical needs - acting as the bridge between market teams, global data platforms, and cross-functional stakeholders.
• Identify 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, semantically tagged, and documented with the context AI models need to interpret them accurately, with explicit consideration for how attributes will be consumed by AI models.
• Support the operationalization of AI products - assisting with data validation, output testing, feedback loops, and continuous improvement of AI-generated insights.
• Actively leverage AI tools (e.g., Copilot, GenAI assistants, n8n, automation scripts) in daily work to increase efficiency, reduce manual effort, and improve output quality - serving as a role model for AI-augmented operations.
• Identify and implement automation opportunities within data operations - proposing where AI or rule-based automation can replace repetitive manual tasks in mapping, validation, and quality checks.
• Create and maintain operational documentation - including process SOPs, mapping logic, vendor feed specifications, data dictionaries, and troubleshooting guides - written with clarity and structure that supports both human users and AI system context layers, ensuring institutional knowledge is captured in formats that enable AI tools to leverage it.
• Support onboarding and training of colleagues on data tools, standards, AI-enabled workflows, and processes - and contribute to continuous improvement by flagging recurring pain points and proposing process enhancements.

Key Working Relation:

• Global Market Data & AI Acceleration Lead
• 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, This is your opportunity to tackle the world’s biggest challenges with us: Maintaining our health, feeding growing populations and slowing the rate of climate change. You have a voice, ideas and perspectives and we want to hear them. Because our success begins with you. Be part of something big. Be Bayer.

• Bachelor’s degree in Business, Economics, Data Analytics, Information Management, or related field.
• 2-5 years of experience in data operations, data quality management, business analytics support, or commercial data analytics - ideally in FMCG, Consumer Health, or Pharmaceuticals.
• Hands-on experience with syndicated market data (IQVIA, NielsenIQ, GfK) - including familiarity with data structures, delivery formats, and common quality issues - is a plus.
• Experience defining and applying data mapping rules, product matching logic, and classification standards.
• Strong analytical and problem-solving skills - ability to investigate data issues systematically and drive resolution.
• Proficiency in Excel; familiarity with SQL, Power BI, Azure, Databricks, workflow tools, scripting basics, or prompt engineering 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, learning.
• Interest in or hands-on exposure to automation concepts (e.g., scripting, workflow tools, AI-assisted data processes, prompt engineering basics).
• Detail-oriented with strong organizational skills and ability to manage multiple parallel workstreams.
• Experience creating process documentation, SOPs, and training materials.
• Effective communicator - able to work across cultures and functions, explain data issues clearly to non-technical stakeholders.
• Proactive, self-directed, and comfortable working in a global, matrixed environment.
• Growth mindset - views AI not as a threat but as a multiplier, and actively seeks to integrate AI into personal workflows and team processes.
• Fluent English required; additional languages a plus.

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.