Data Analyst

Job Title: Data Analyst

Career Level - C3

Introduction to role:

The Data Analytics Lead is expected to have a strong Subject Matter Expertise around Operations Data objects and will be involved in the evolution of Ops Data Office Advanced Analytics services to elevate data scientists to generate higher levels of insight and competitive advantage. You will stay updated on industry trends and collaborate on the latest advancements in AI research, applying new findings to ongoing and continuous improvement projects. Ensure ethical AI & advanced analytics development practices, transparency, and privacy requirements are met.

Accountabilities:

• Work collaboratively with stakeholders to develop clear, compelling requirements of analytic delivery and insights.

• Responsible for co-creating prototypes working with data scientists on validating proposed ideas and soliciting input from stakeholders, running test-driven development and continuous integration processes, support, and troubleshooting.

• Act as a subject matter expert in advanced analytics and bring best-in-class, innovative ideas to test and measure performance and impact on business requirements.

• Define creative solutions to business problems using advanced algorithms and models. Build and manage a high-performing team.

• Make business recommendations to senior leadership based on results/trends identified in data analysis.

• Responsible for setting and operationalizing the analytics strategy for the data office organization.

• Partner with the data engineering team, technology architects, and IT to build & deploy Machine Learning/AI pipelines that enable analytics reusable framework & algorithms.

• Define approaches and lead complex and cross-functional analytical projects leveraging advanced computational algorithms.

• Lead initiatives involving exploration and analysis of data across platforms.

• Evolve iterative development processes to drive timely Data Science outcomes and reinforce the test-and-learn culture.

• Define best practices, identify gaps, improve quality, and share advanced modeling techniques and learnings.

• Use relevant knowledge of computer science fundamentals, distributed computing, and machine learning to help build scalable analytical solutions.

Essential Skills/Experience:

• Experience in Operations, manufacturing or related field.

• Bachelor's degree in Engineering, Computer Science, Mathematics, Statistics, with 7+ years experience in Operations data and 3+ years in data analytics, data structures, and data science.

• Storytelling capability of creativity, pragmatism, and out-of-the-box thinking.

• Proactive approach with hands-on/can-do mindset, with prototyping/modeling techniques.

• Experience with varied qualitative and quantitative research methods, sampling methodologies, and design thinking.

• Analytical thinking for assessing model performance, interpreting outcomes, and making data-driven decisions for model improvement.

• Demonstrated ability to provide actionable insights that move the business forward exponentially.

• Own all phases of the data science product lifecycle (exploratory data analysis, model development, model productionizing, rollout, and evaluation).

• Demonstrated knowledge of generative models (GANs, VAEs) and NLP.

• Solid understanding of machine learning algorithms and data pre-processing techniques.

• Excellent communication skills with experience presenting and communicating to leadership and stakeholders.

• Fluency in analytical & computational techniques with advanced analytics software package deployment.

Desirable Skills/Experience:

NA

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. Join us in our unique and ambitious world.

AstraZeneca offers an environment where you can embrace constant challenges as intellectually stimulating opportunities to learn more. We keep pushing boundaries as we work on implementing the best systems with cutting-edge science and manufacturing. Our resilience helps us thrive as we innovate and evolve. Here, you will be part of a safe space where ideas are welcomed and rewarded. We actively participate by sharing ideas and problem-solving as a team united behind a common goal to succeed.

Ready to make a big impact? Apply now!

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.