Position:
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Data Scientist
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Entry-level, suitable for candidates with 0 to 3 years of experience
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Focus on real-world data application, AI models, and ML deployment
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Opportunity to contribute to healthcare innovation using modern tools
Company:
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AstraZeneca
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A globally recognized biopharmaceutical company
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Known for developing and delivering life-changing medicines
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Active in over 100 countries with a strong presence in India
Location:
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Bengaluru, Karnataka, India
Job type:
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Full-time
Job mode:
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Hybrid (minimum 3 days/week in office)
Job requisition id:
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R-221088
Years of experience:
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0 to 3 years
Company Description:
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AstraZeneca is a global leader in the biopharmaceutical space, known for its commitment to advancing science and healthcare.
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The company focuses on prescription medicines across Oncology, Cardiovascular, Renal, Metabolism, and Respiratory areas.
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With over 10,000 employees in research and development, AstraZeneca is constantly innovating.
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The company fosters a collaborative culture and values diversity, inclusion, and continuous learning.
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AstraZeneca believes in the transformative power of data and AI, applying them in multiple verticals to drive breakthroughs in patient care.
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With cutting-edge infrastructure and a dynamic work environment, AstraZeneca is helping define the future of healthcare.
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The Bengaluru office serves as a key tech and analytics hub for AstraZeneca's global operations.
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Employees have access to advanced tools and leadership support to create impactful solutions across the business.
Profile Overview:
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This role is ideal for individuals who enjoy solving real-world business and scientific problems through data.
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The selected candidate will be responsible for using data science techniques such as machine learning, statistical modeling, and NLP.
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You will be collaborating with cross-functional teams to build and deliver solutions that impact scientific research and business decisions.
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You will interpret data, identify trends, and generate meaningful insights for high-impact projects.
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The role involves working on varied data sources including structured, unstructured, and multimodal data.
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You’ll contribute to new AI-driven strategies in drug discovery, clinical trials, and commercial functions.
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Your expertise will support decision-making by creating reproducible, high-quality models and algorithms.
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You’ll also contribute by coaching team members and enhancing data science capabilities across teams.
Qualifications:
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A Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a closely related field is required.
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Strong grasp of statistics, probability, and data modeling principles.
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Demonstrated ability to work with real-world datasets and build ML models from scratch.
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Proficiency in Python, with hands-on knowledge of Scikit-learn, TensorFlow, or similar libraries.
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Experience working with data visualization platforms such as Tableau or Power BI.
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Familiarity with big data environments like Hadoop or Spark is a plus.
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Should be comfortable working in a team and also taking ownership of individual deliverables.
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Effective communication and storytelling ability with stakeholders is essential.
Additional Info:
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This is a high-impact role offering the chance to work on projects that influence strategic decisions.
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The company promotes in-person collaboration for fast-paced and high-quality output but remains flexible for individual circumstances.
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You’ll be exposed to data science applications in the fields of genomics, clinical development, and commercial operations.
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There is strong encouragement for publishing work, attending conferences, and building visibility in the data science community.
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The team consists of experienced data professionals who foster a supportive and learning-centric culture.
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You’ll get access to state-of-the-art tools, cloud-based platforms, and continuous learning opportunities.
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AstraZeneca values personal growth and offers career development opportunities through internal mobility and learning resources.
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You’ll be making a real-world impact through your work while being supported by global leaders in science and technology.
Roles and Responsibilities:
Data Handling and Analysis
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Work on a variety of complex datasets using statistical analysis, ML models, and pattern recognition techniques.
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Design and implement end-to-end data pipelines including preprocessing, feature engineering, and validation.
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Integrate structured and unstructured data from internal systems and external sources.
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Convert business needs into actionable data science problems and propose suitable solutions.
Model Development and Deployment
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Build and deploy machine learning models including regression, classification, and clustering techniques.
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Apply natural language processing, computer vision, graph theory, and other advanced AI concepts as needed.
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Ensure all models are tested, validated, and deployed in production-grade environments.
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Use cloud-based platforms and open-source libraries to build scalable solutions.
Collaboration and Communication
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Partner with stakeholders to understand data requirements and translate them into technical implementations.
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Collaborate with software engineers, product owners, and business leaders to ensure alignment.
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Present insights and solutions in an accessible format for non-technical stakeholders.
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Communicate uncertainties, assumptions, and caveats clearly in reports and presentations.
Research and Innovation
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Conduct research to enhance existing models or develop new ones for better performance and scalability.
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Stay up to date with advancements in machine learning, AI, and data science tools.
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Explore novel algorithms that fit unique business challenges where standard solutions fall short.
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Contribute to knowledge-sharing sessions and internal data science forums.
Training and Mentoring
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Offer guidance to junior data scientists and analysts.
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Provide internal training sessions on topics such as model interpretation, best practices, and tool usage.
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Act as a go-to resource for key data science techniques and platforms within the team.
Please click here to apply.
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