Senior Specialist, Data Scientist at AstraZeneca

Durham, North Carolina, United States -

Full Time

Start Date

Immediate

Expiry Date

21 Mar, 26

Salary

0.0

Posted On

21 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Python, SQL, NoSQL, ETL, Power BI, Statistical Inference, Model Evaluation, Agile Delivery, MLOps, Data Engineering, Analytical Skills, Communication, Critical Thinking, Problem Solving

Industry

Pharmaceutical Manufacturing

Description

The Role Join the Operational Data Strategy (ODS) team to turn clinical operations data into action and help AstraZeneca deliver 20 new medicines by 2030 while reducing ~$300M in waste; you’ll develop advanced analyses and machine‑learning models (dashboards in Power BI are for storytelling, not the core output) that power end‑to‑end aggregated planning—one unified view that sharpens prioritization, flags risks earlier, accelerates trade‑offs, and aligns clinical demand and supply; reporting to the Strategic Analytics & Enablement Lead, you’ll shape how R&D data is collected, organized, validated, and analyzed, driving portfolio‑wide transparency and evidence‑based decisions while exemplifying critical thinking, a growth mindset, grit, and resilience, and mentoring peers through high‑quality delivery. In this role, you will Deliver scalable, well-governed analytics: translate operational needs into robust analyses and ML models; use dashboards for storytelling. Own the end-to-end workflow: frame hypotheses, source and prep data (DBs/APIs/files), run exploratory/descriptive/predictive analyses, and present clear, actionable insights. Ensure quality and speed: apply reviews and source checks, state assumptions/limits, stay in scope, and respond to ad hoc requests with timely outputs. Partner and enable work with data engineering on ETL, train users, share best practices, and build adoption of ODS analytics. Grow and lead by example: stay current on methods/tools and model integrity, initiative, adaptability, organization, and strategic thinking. Education, Qualifications, Skills and Experience Essential Bachelor’s degree in computer science, data/analytics, statistics, engineering, or related field; 3+ years’ experience. Advanced hands-on with Python and visualization (Power BI, Spotfire); track record delivering advanced analytics, not just dashboards. Proficient with SQL/NoSQL, ETL, cloud platforms, and software best practices (reproducibility, version control). Proven complex analysis in business/scientific domains, including Clinical Operations. Strong grasp of data science, ML algorithms, statistical inference, and model evaluation. Clear written and verbal English; able to explain assumptions, uncertainties, and limitations. Desired Experience in Agile delivery and exposure to modern MLOps. Evidence of improving processes, documentation, quality standards, and driving stakeholder adoption. Are you interested in working at AZ, apply today! AstraZeneca is an equal opportunity employer that is committed to diversity and inclusion and providing a workplace that is free from discrimination. AstraZeneca is committed to accommodating persons with disabilities. Such accommodation is available on request in respect of all aspects of the recruitment, assessment and selection process and may be requested by emailing AZCHumanResources@astrazeneca.com. #LI-Hybrid Date Posted 20-Dec-2025 Closing Date 04-Jan-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. AstraZeneca is a global, science-led, patient-focused biopharmaceutical company. We focus on discovering, developing and commercialising prescription medicines for some of the world’s most serious diseases. But we are more than one of the world’s leading pharmaceutical companies. At AstraZeneca, we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science, challenge convention and unleash your entrepreneurial spirit. To embrace differences and take bold actions to drive the change needed to meet global healthcare and sustainability challenges. There is no better place to make a difference in medicine, patients, and society. An inclusive culture where you will connect different thinking to generate new and valuable opportunities. Where you will find a commitment to lifelong learning, growth and development for all. Our Inclusion & Diversity (I&D) mission is to create an inclusive and equitable environment where people belong, using the power of our diversity to push the boundaries of science to deliver life-changing medicines to patients. Inclusion and diversity are fundamental to the success of our company, because innovation requires breakthrough ideas that only come from a diverse workforce empowered to challenge conventional thinking. We’re curious about science and the advancement of knowledge. We find creative ways to approach new challenges. We’re driven to make the right choices and be accountable for our actions. As an organisation centred around what makes us human, we put a big focus on people. Across our business, we want colleagues to wake up excited about their day at the office, in the field, or in the lab. Along with our purpose to bring life-changing medicines to people across the globe, we have a promise to you: to help you realise the full breadth of your potential. Here, you’ll do work that has the potential to change your life and improve countless others. And, together with your team, you’ll shape a culture that unites and inspires us every day. This is your life at AstraZeneca.

Responsibilities

You will develop advanced analyses and machine-learning models to enhance clinical operations data. This includes owning the end-to-end workflow from data sourcing to presenting actionable insights.