Lead Associate Data Intelligence

该职位来源于猎聘

• Business Engagement &
• Relation: Proactively establish and maintain strong collaborative relationships with key business stakeholders (e.g., Business Unit, Medical, Business Excellence). Thoroughly research, gather, structure, and validate business analytics requirements and pain points. Evaluate the business requirement rationale and play the role of proactive business partner & advisor beyond responsive business supporter. Precisely translate business requirements into actionable technical specifications and data solution blueprints.

Report

Development &

• Delivery management: Lead and manage Power BI and Mobile BI developers, creating development plans and assigning tasks. Oversee the design, development, testing, deployment, and optimization of Power BI reports & dashboards, and Mobile BI applications. Ensure delivered reports/analytics are accurate, timely, and intuitive, meeting business decision-making needs. Enforce data visualization best practices to enhance user experience and self-service analytics capabilities. Drive

AI+BI initiative: Promote the adoption of intelligent, self-service analytics across the company by leveraging popular LLMs and AI agents to enable business users to explore data and generate insights independently. Design and deploy AI-powered analytics solutions—such as provide natural-language querying, build LLM agent-based workflows, deploy conversational BI assistants, and enable automated reporting—integrated with existing BI platforms.

Project Management: Manage the full lifecycle of BI report development projects, ensuring timely and high-quality completion. Manage the BI development team(outsourced resource), including guidance, performance evaluation, and skills development. Effectively coordinate human and financial resources internally and externally.

Perform lean tracking of project progress in each phase, milestone and tasks, ensuring all the issues, change, sign-off and documents are well maintained in the PM tool. Data

Management &

• Solution Optimization: Be proactively involved in data governance management including data quality management ,report & data ownership clarification, access privilege management, metadata &
• KPI definition & documentation. Understand underlying data sources and models with close collaborating with data engineering team to ensure data reliability & consistency. Stay abreast of BI technology trends (especially Power BI ecosystem), evaluating and implementing new tools/methods to enhance analytical efficiency. User Training &
• Support: Provide essential user training on Power BI / Mobile BI to end business users, facilitating self-service analytics adoption. Perform report maintenance and operation, timely respond to user inquiry , feedback or request and driving iterative enhancement 任职要求： 教育水平

Bachelor’s degree or higher in Computer Science, Information Technology, Statistics, Mathematics, Business Analytics, or related fields. 相关领域工作经验及年限

Minimum 7 years’experience of data reporting & dashboard field in pharma industry. Proven experience (＞ 2 years) in project management, or a senior technical lead role.

Expert Power BI Proficiency: hands-on experience of developing and deploying Power BI solution. Deep understanding of DAX, data modeling, and visualization best practices 语言水平

Proficiency in written and spoken English. 能力要求

Familiarity with pharma industry specific data categories and business domains such as HCO, HCP, DDI Data Flow,

Territory &

• Target, CPA/CPT, CHPA, CRM ,Event, Expense etc. Sensitive understanding on regulatory requirements and industry standards in the pharmaceutical sector, particularly in China. Strong logic-thinking capability and high sense of potential risk and defect identification.

Experience in developing AI-enabled BI project experience is a valuable plus.

Excellent communication skills and collaboration mindset, has ability to manage user's requirement and maintain good working relationship 计算机水平

Extensive experience in

Power BI, Mobile BI ,SQL, data modeling. Knowledge of ETL (Extract, Transform, Load) processes and system architecture.