AstraZeneca Recruitment 2025 Hiring Data Scientist

AstraZeneca Recruitment 2025 Hiring Data Scientist

AstraZeneca Recruitment 2025 is now hiring talented Data Scientists to join its cutting-edge global research and technology teams. This is a unique opportunity to work at the forefront of healthcare innovation, leveraging AI, machine learning, and advanced analytics to accelerate drug discovery and improve patient outcomes. As a Data Scientist at AstraZeneca, you’ll collaborate with multidisciplinary teams, solve real-world problems, and contribute to life-changing scientific breakthroughs. If you’re passionate about data and healthcare, apply now to shape the future of medicine with AstraZeneca.

Company Name: AstraZeneca

Job Profile: Data Scientist

Degree Needed: B.E/B.Tech/M.E/M.Tech

Passout Year: 2024, 2025

Work Location: Bangalore, India

Experience Level: 0 – 1 Year

Essential Skills/Experience:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Demonstrable experience in data analysis and machine learning projects.
• Proficiency in programming languages such as Python and experience with ML libraries like TensorFlow or Scikit-learn.
• Strong knowledge of data visualization tools, e.g., Tableau, PowerBI
• Experience with big data technologies, such as Hadoop or Spark..
• Excellent problem-solving skills and attention to detail.
• Good communication skills and ability to interpret data analytics into actionable insights.

Desirable Skills/Experience:

• Experience in enterprise-level integrations and data engineering projects.
• Familiarity with data visualization tools such as Tableau or Power BI

Accountabilities:

• Review and develop working practices to ensure that data science work is delivered to robust quality standards
• Interpret and analyze complex datasets using statistical and machine learning techniques.
• Collaborate with various teams to understand data needs and contribute to data-driven strategies.
• Coordinate the implementation of novel modelling solutions designed to drive the interrogation of datasets for insights in scientific and business application areas within defined project scope. This includes integrating complex data from multiple different sources and modalities includes the application of specialized approaches in classification, regression, clustering, NLP, image analysis, graph theory and/or other techniques.
• Using domain-specific understanding, translates unstructured, complex business problems into the appropriate data problem, model and analytical solutions
• Researches and develops advanced predictive models and computational methods to guide and shape decision-making within the project scope.
• Provide training and advice to collaborators on optimal use of key data, analysis platforms and the appropriate use of data science.
• Apply expert AI research techniques, including establishment of hypotheses that can be approached using computational methods and tools. Present or publish findings for conferences and in peer reviewed journals.
• Build and manage effective relationships with stakeholders to ensure utilization and value of information resources and services. Clearly and objectively communicate results, as well as their associated uncertainties and limitations to shape solutions
• Provide advanced data science expertise to cross-functional projects and shape delivery of data science solutions that drive value to AstraZeneca
• Apply a range of data science methodologies, developing novel data science solutions where off-the-shelf methodologies do not fit
• Develop, implement and maintain required tools and algorithms in a manner which meets regulatory and evidential requirements within project scope
• Leads data science projects of defined scope and provide coaching for  team members
• Developing, maintaining and applying ongoing knowledge and awareness in trends, standard methodology and new developments in analytics and data science
• Develop, test, and deploy machine learning models to solve business problems.
• Present data insights and models to stakeholders with clarity and effectiveness.
• Continuously evaluate data models and tools to enhance data accuracy and performance.
• Mentor and provide guidance to other team m

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