Insights & Analytics Specialist

AstraZeneca•Gaithersburg, MD

18h•$72,121 - $108,181•Hybrid

About The Position

The Insights & Analytics Specialist helps transform data, business processes, and emerging AI technologies into trusted insights and scalable solutions that improve scientific and business decision-making. Working across business, technology, analytics, and governance functions, the role combines data analysis, data management, process improvement, and AI-enabled innovation to deliver measurable business value. The successful candidate will help identify opportunities for analytics, automation, and AI adoption while ensuring that solutions are scalable, compliant, and aligned with organizational standards. This role is ideal for someone who enjoys solving complex business problems, connecting people and technology, and helping modern analytical and AI capabilities move from experimentation into practical operational use.

Requirements

Bachelor's degree in Computer Science, Data Science, Data Management, Information Systems, Statistics, Mathematics, Engineering, or a related discipline.
At least 1 year of experience performing data analysis, reporting, analytics, or business intelligence activities.
At least 1 year of experience using Python, SQL, R, databases, visualization platforms, or similar analytical tools.
Understanding of data quality, governance, metadata management, and data stewardship principles.
Familiarity with generative AI tools, AI assistants, AI agents, workflow automation, or related technologies.
Exposure to cloud-based analytics environments, preferably Microsoft Azure or AWS.
Ability to translate business needs into practical data, analytics, automation, or AI-enabled solutions.
Strong communication, consulting, and stakeholder engagement skills.
Ability to work effectively in cross-functional teams.

Nice To Haves

Experience building, configuring, or supporting AI agents, copilots, workflow automation solutions, or AI-enabled business processes.
Experience supporting deployment, operationalization, or monitoring of analytics and AI solutions.
Familiarity with Git, testing, CI/CD, APIs, and modern software engineering practices.
Experience working across business, technology, governance, quality, or data science functions.
Experience driving adoption of new technologies through training, enablement, and change management.
Experience in pharmaceuticals, life sciences, healthcare, or another regulated environment.

Responsibilities

Translate business and scientific needs into solutions: Partner with stakeholders to understand challenges, define requirements, and deliver data, analytics, automation, and AI-enabled solutions.
Perform data analysis and integration: Analyze, profile, transform, and integrate data to support reporting, analytics, AI applications, and data science initiatives.
Drive AI-enabled business transformation: Identify opportunities to improve scientific and business workflows through analytics, automation, AI agents, and process redesign, delivering scalable solutions that improve efficiency and business outcomes.
Develop and operationalize AI-enabled solutions: Contribute to the design, deployment, monitoring, and continuous improvement of AI-assisted analytics, AI agents, and automated workflows, leveraging cloud-based platforms where appropriate.
Bridge business, data, and technology: Collaborate across business, technology, data science, engineering, and governance teams to translate complex needs into practical, scalable solutions and support successful adoption.
Maintain data quality, governance, and compliance: Apply data governance, metadata management, privacy, security, and quality standards to ensure trusted, compliant, and fit-for-purpose data and solutions.
Communicate insights effectively: Present findings, recommendations, assumptions, limitations, and business implications clearly to technical and non-technical audiences.