AstraZeneca is hiring for an fresher entry level Data Scientist role in India

Position:

• Data Scientist

• Entry-level, suitable for candidates with 0 to 3 years of experience

• Focus on real-world data application, AI models, and ML deployment

• Opportunity to contribute to healthcare innovation using modern tools

Company:

• AstraZeneca

• A globally recognized biopharmaceutical company

• Known for developing and delivering life-changing medicines

• Active in over 100 countries with a strong presence in India

Location:

• Bengaluru, Karnataka, India

Job type:

• Full-time

Job mode:

• Hybrid (minimum 3 days/week in office)

Job requisition id:

• R-221088

Years of experience:

• 0 to 3 years

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Company Description:

• AstraZeneca is a global leader in the biopharmaceutical space, known for its commitment to advancing science and healthcare.

• The company focuses on prescription medicines across Oncology, Cardiovascular, Renal, Metabolism, and Respiratory areas.

• With over 10,000 employees in research and development, AstraZeneca is constantly innovating.

• The company fosters a collaborative culture and values diversity, inclusion, and continuous learning.

• AstraZeneca believes in the transformative power of data and AI, applying them in multiple verticals to drive breakthroughs in patient care.

• With cutting-edge infrastructure and a dynamic work environment, AstraZeneca is helping define the future of healthcare.

• The Bengaluru office serves as a key tech and analytics hub for AstraZeneca's global operations.

• Employees have access to advanced tools and leadership support to create impactful solutions across the business.

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Profile Overview:

• This role is ideal for individuals who enjoy solving real-world business and scientific problems through data.

• The selected candidate will be responsible for using data science techniques such as machine learning, statistical modeling, and NLP.

• You will be collaborating with cross-functional teams to build and deliver solutions that impact scientific research and business decisions.

• You will interpret data, identify trends, and generate meaningful insights for high-impact projects.

• The role involves working on varied data sources including structured, unstructured, and multimodal data.

• You’ll contribute to new AI-driven strategies in drug discovery, clinical trials, and commercial functions.

• Your expertise will support decision-making by creating reproducible, high-quality models and algorithms.

• You’ll also contribute by coaching team members and enhancing data science capabilities across teams.

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Qualifications:

• A Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a closely related field is required.

• Strong grasp of statistics, probability, and data modeling principles.

• Demonstrated ability to work with real-world datasets and build ML models from scratch.

• Proficiency in Python, with hands-on knowledge of Scikit-learn, TensorFlow, or similar libraries.

• Experience working with data visualization platforms such as Tableau or Power BI.

• Familiarity with big data environments like Hadoop or Spark is a plus.

• Should be comfortable working in a team and also taking ownership of individual deliverables.

• Effective communication and storytelling ability with stakeholders is essential.

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Additional Info:

• This is a high-impact role offering the chance to work on projects that influence strategic decisions.

• The company promotes in-person collaboration for fast-paced and high-quality output but remains flexible for individual circumstances.

• You’ll be exposed to data science applications in the fields of genomics, clinical development, and commercial operations.

• There is strong encouragement for publishing work, attending conferences, and building visibility in the data science community.

• The team consists of experienced data professionals who foster a supportive and learning-centric culture.

• You’ll get access to state-of-the-art tools, cloud-based platforms, and continuous learning opportunities.

• AstraZeneca values personal growth and offers career development opportunities through internal mobility and learning resources.

• You’ll be making a real-world impact through your work while being supported by global leaders in science and technology.

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Roles and Responsibilities:

Data Handling and Analysis

• Work on a variety of complex datasets using statistical analysis, ML models, and pattern recognition techniques.

• Design and implement end-to-end data pipelines including preprocessing, feature engineering, and validation.

• Integrate structured and unstructured data from internal systems and external sources.

• Convert business needs into actionable data science problems and propose suitable solutions.

Model Development and Deployment

• Build and deploy machine learning models including regression, classification, and clustering techniques.

• Apply natural language processing, computer vision, graph theory, and other advanced AI concepts as needed.

• Ensure all models are tested, validated, and deployed in production-grade environments.

• Use cloud-based platforms and open-source libraries to build scalable solutions.

Collaboration and Communication

• Partner with stakeholders to understand data requirements and translate them into technical implementations.

• Collaborate with software engineers, product owners, and business leaders to ensure alignment.

• Present insights and solutions in an accessible format for non-technical stakeholders.

• Communicate uncertainties, assumptions, and caveats clearly in reports and presentations.

Research and Innovation

• Conduct research to enhance existing models or develop new ones for better performance and scalability.

• Stay up to date with advancements in machine learning, AI, and data science tools.

• Explore novel algorithms that fit unique business challenges where standard solutions fall short.

• Contribute to knowledge-sharing sessions and internal data science forums.

Training and Mentoring

• Offer guidance to junior data scientists and analysts.

• Provide internal training sessions on topics such as model interpretation, best practices, and tool usage.

• Act as a go-to resource for key data science techniques and platforms within the team.

Please click here to apply.