Insights & Analytics Specialist

Reposted Yesterday
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Gaithersburg, MD, USA
In-Office
94K-141K Annually
Senior level
Biotech • Pharmaceutical
The Role
Designs, develops, and deploys production-ready machine learning solutions across the ML lifecycle. Works with stakeholders to define problems, builds and evaluates models (including NLP and computer vision), applies generative AI where appropriate, uses cloud and MLOps practices, and ensures model quality, governance, and clear communication.
Summary Generated by Built In

Location: Gaithersburg, USA

Hybrid: 3 days a week onsite


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 us. 


Typical Accountabilities

  • 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.

Qualifications and Skills

Essential

  • 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.

Desirable

  • 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.

The annual base pay for this position ranges from $72,120.80 - $108,181.20 USD. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.


Are you ready to be part of a talented, cross-functional team working together to improve lives and make the biggest possible impact for patients, science and society?


Why AstraZeneca? 

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility.


Apply now!


Date Posted

08-Oct-2026

Closing Date

14-Oct-2026

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

Skills Required

  • Bachelor's degree in Computer Science, Data Science, AI, Engineering, Mathematics, Statistics, or related field, or equivalent professional experience
  • Typically at least five years of experience as a Data Scientist, Machine Learning Engineer, AI Engineer, or related role
  • Demonstrated experience taking ML work from problem definition and data preparation through model evaluation and deployment/operational use
  • Experience working with text, images, or other unstructured data; experience with NLP or computer vision and modern deep learning architectures (including attention and transformer-based models)
  • Strong programming experience in Python, writing maintainable, tested, reusable code
  • Experience working with databases, APIs, and data pipelines
  • Experience using at least one major cloud platform (preferably AWS or Microsoft Azure) for ML development, training, deployment, or operations
  • Experience with Docker and familiarity with software engineering and MLOps practices (version control, testing, deployment automation, experiment tracking, monitoring, model lifecycle management)
  • Experience in healthcare, pharmaceuticals, life sciences, or another regulated and data-intensive environment
  • Ability to communicate technical findings to technical and non-technical audiences and provide technical leadership/mentoring

AstraZeneca Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AstraZeneca and has not been reviewed or approved by AstraZeneca.

  • Fair & Transparent Compensation — Pay is considered competitive across many roles when total rewards are factored in. Senior scientific and leadership bands are described with high ranges that reinforce competitiveness at upper levels.
  • Strong & Reliable Incentives — Bonuses, equity eligibility in many salaried roles, and solid sales on‑target earnings with upside are emphasized as meaningful parts of compensation. These elements boost overall value even where base pay is not the very highest.
  • Retirement Support — A 401(k) program with a strong company match and immediate vesting is repeatedly cited as a standout. Generous retirement support is viewed as enhancing the total package relative to peers.

AstraZeneca Insights

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The Company
HQ: Gaithersburg, MD
70,000 Employees
Year Founded: 1999

What We Do

We're transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet.

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