AI Data Analyst

AI Data Analyst

As a Data Intelligence Analyst, you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative and diverse people around the world. Here, you will make an impact by:

• Design, develop, and deliver scalable Power BI dashboards and semantic models using capabilities such as Dataflows Gen2, Direct Lake, and AI-assisted analytics to provide actionable insights to leadership.
• Develop and optimize data pipelines using SQL, Python (Pandas/PySpark), and modern data-processing frameworks, enabling ingestion, transformation, and analysis of structured and unstructured data.
• Architect and manage cloud data solutions leveraging Snowflake, Azure Synapse, Microsoft Fabric, or Databricks, ensuring high-performance data modeling and efficient ingestion for analytics and AI use cases.
• Design, operationalize, and evaluate AI/ML solutions, including predictive analytics, anomaly detection, classification, forecasting, natural language processing, and Copilot-enabled analytics.
• Build and integrate generative AI, AI agents, and copilots into enterprise workflows using structured and unstructured data and approved platforms such as Azure AI Foundry, Copilot Studio, Azure OpenAI, AWS Bedrock, or similar technologies.
• Develop API- and JSON-based integrations and data pipelines connecting enterprise platforms—including Salesforce, SAP, and external regulatory platforms—to analytics, AI/ML, and agent-driven workflows.
• Establish and apply data and AI governance practices—including data quality, metadata management, lineage, responsible AI, and enterprise standards—in collaboration with Quality, Regulatory, IT, and Data Governance teams.
• Partner with business, Master Data, and digital transformation teams to define data products, KPIs, and AI-driven insights that support Healthcare and Regulatory operations.
• Enable self-service analytics and AI adoption by training users on Power BI, Copilot, and data tools; promote best practices in data literacy and responsible AI usage.

To set you up for success in this role from day one, Solventum requires (at a minimum) the following qualifications: Bachelor's degree or higher (completed and verified prior to start) in Computer Science, Data Science, Engineering, Statistics, Information Systems, or a related field from an accredited institution AND Seven (7) years of experience in data analytics, business intelligence, data engineering, or data science roles with demonstrated impact delivering data-driven insights.

In addition to the above requirements, the following are also required: Hands-on experience with data visualization tools such as Power BI (including DAX, data modeling, and dashboard design); familiarity with Microsoft Fabric, Copilot, or embedded analytics. Experience working with modern data platforms such as Snowflake, Databricks, Azure Synapse, or Microsoft Fabric, including data ingestion and transformation. Proficiency in SQL and at least one programming language (Python preferred) for data manipulation, automation, and analysis (e.g., Pandas, PySpark). Hands-on experience developing, implementing, or supporting AI/ML solutions using Python or R.

Additional qualifications that could help you succeed even further in this role include: Master's degree in Computer Science, Data Science, Mathematics, Statistics, Finance, or a related quantitative field. Experience developing generative AI, retrieval-augmented generation, or agentic AI solutions and integrating them with enterprise data platforms and business applications, preferably in regulated environments. Understanding of data governance, data quality, and metadata management principles within enterprise environments. Demonstrated curiosity and ability to quickly learn, evaluate, and apply emerging AI technologies to solve business problems and deliver measurable value.