AstraZeneca

Healthcare

SeniorSpecialist,DataScienceOperationalDataStrategy(ODS)

$220–330k ~AI est. Warsaw, Poland FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Specialist, Data Science — Operational Data Strategy (ODS) at AstraZeneca. Skills: Data Science, Predictive Modeling, Data Visualization, Machine Learning. Coordinate implementation of analytical solutions. Coordinate implementation of data visualization solutions”

What You'll Achieve.

Create tangible impact in clinical operations

Industry & Context.

Healthcare
Problems you'll solve

Critical thinking; Hypotheses development; Data-driven decision making

What They're Looking For.

Must Have

Bachelor's degree in computer science, data analysis, statistics, engineering, or a related discipline, Master's degree in computer science, data analysis, statistics, applied mathematics, or a relevant discipline, Expert knowledge of analytics and visualization tools, Familiarity with database systems (SQL and NoSQL), Familiarity with ETL pipelines, Familiarity with cloud environments, Familiarity with software development best practices, Demonstrated experience developing complex data analyses, Excellent written and verbal communication skills in English, Understanding of data science principles, Understanding of machine learning algorithms, Understanding of statistical inference, Understanding of model evaluation methodologies

Nice to Have

Experience working in Agile delivery environments, Exposure to modern MLOps practices, Evidence of process improvement, Evidence of standard setting across analytics workflows, Evidence of model governance, Evidence of stakeholder adoption

What You'll Do.

Coordinate implementation of analytical solutions

Coordinate implementation of data visualization solutions

Ensure scalability of solutions

Ensure reproducibility of solutions

Ensure clear governance of solutions

Develop solutions to business challenges

Develop solutions to analytics challenges

Translate operational needs into data science deliverables

Lead advanced analytics approaches

Lead visualization approaches

Respond to ad hoc queries

Provide timely analytical outputs

Provide accurate analytical outputs

Articulate assumptions

Articulate limitations

Design strategic analytics plans

Align plans to program objectives

Align plans to portfolio objectives

Identify relevant data sources

Evaluate relevant data sources

Synthesize quantitative insights

Synthesize qualitative insights

Design machine learning models

Implement machine learning models

Evaluate machine learning models

Maintain high quality standards

Enforce quality reviews

Align analysis to hypotheses

Develop analytics trends knowledge

Apply analytics trends knowledge

Develop methodologies knowledge

Apply methodologies knowledge

Guide ODS best practices

Define best practices for data collection

Define best practices for data preprocessing

Partner on ETL handoffs

Partner on data engineering handoffs

Compile insights into figures

Compile insights into charts

Compile insights into tables

Craft concise narratives

Present complex work to principals

Present complex work to cross-functional teams

Engage dynamically with feedback

Tailor content to varied audiences

Coach specialists on communication

Build effective relationships

Manage effective relationships

Ensure utilization of ODS

Provide training on data use

Provide advice on data use

Provide training on analysis use

Provide advice on analysis use

Practice upward management

Provide timely progress updates

Provide comprehensive progress updates

Own workstreams end-to-end

Guide others to own workstreams

How You'll Work.

Team & Collaboration

Cross-functional teams; Senior stakeholders; Principals; Cross-functional engagement

Communication Scope

Written communication; Verbal communication; Clear communication; Executive presentations; Tailor content

Process & Methodology

Agile delivery environments, Workstream management

Full Job Description

**Location:** Warsaw, Poland **Hybrid model of work:** 3 days in office, 2 remote per week The Operational Data Strategy (ODS) function provides strategic oversight for how clinical operations data is collected, organized, validated, and analyzed across R&D. ODS combines advanced database and system capabilities with innovative data science methodologies to enable visual, data-driven decision making in clinical operations. ODS is a key division within R&D at AstraZeneca that partners across BioPharma to elevate evidence generation and operational excellence. We are seeking a Senior Specialist, Data Science to be a key asset within ODS, reporting to the Strategic Analytics and Enablement Lead. You will drive complex analytics programs, design and implement predictive models, and translate business needs into rigorous data science solutions that create tangible impact in clinical operations. Core deliverables emphasize advanced analytics outputs and AI/ML applications; dashboards in Power BI are supportive rather than central. You will embody our core traits—critical thinking, growth mindset, grit, and resilience—while coaching specialists and raising the quality bar across ODS. **Typical Accountabilities** * Coordinate the implementation of analytical and data visualization solutions across clinical operations, ensuring scalability, reproducibility, and clear governance. * Develop solutions to business and analytics challenges using established frameworks and tools, translating complex operational needs into robust data science deliverables. * Lead advanced analytics and visualization approaches that enable data-driven decision making; use dashboards as communication aids when appropriate. * Respond to ad hoc queries from senior stakeholders with timely, accurate analytical outputs and clearly articulated assumptions and limitations. * Frame core issues, develop and refine hypotheses, and design strategic analytics plans aligned to program and portfolio objectives in

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