Position:
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Associate - Data Analyst
Company:
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AstraZeneca
Location:
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Shāhāpur, Maharashtra, India
Job type:
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Full time
Job mode:
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Hybrid, minimum three days per week in office
Job requisition id:
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R-246357
Years of experience:
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0 to 3 years
Company description:
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A global biopharmaceutical organization focused on discovering, developing, and delivering medicines that improve patient outcomes across the world
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Established presence in India for more than four decades, contributing to accessible and sustainable healthcare solutions
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Dedicated to research driven innovation across therapy areas such as oncology, cardiovascular, respiratory, and rare diseases
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Strong emphasis on science led decision making supported by digital transformation and modern analytics infrastructure
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Encourages collaboration across geographies, bringing together teams from research, commercial, technology, and operations
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Invests significantly in technology platforms, cloud ecosystems, and advanced analytics to support smarter and faster decisions
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Committed to ethical standards, compliance, and responsible corporate citizenship in every market it operates
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Actively promotes diversity, equity, and inclusion, ensuring representation from varied backgrounds and perspectives
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Creates an environment where curiosity, accountability, and continuous learning are encouraged
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Aligns business growth with long term sustainability goals for society and the planet
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Offers structured development programs, coaching, and cross functional exposure for early career professionals
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Supports employee wellbeing through initiatives focused on physical, financial, and psychological health
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Recognized for a strong workplace culture that values collaboration and mutual respect
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Encourages employees to contribute ideas that challenge conventional approaches and improve patient impact
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Operates with a clear mission to advance healthcare through science and technology
Profile overview:
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Entry level analytics professional role designed for individuals passionate about data driven decision making
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Responsible for transforming complex datasets into actionable insights that influence strategic and operational choices
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Works closely with cross functional stakeholders to understand business needs and convert them into analytical solutions
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Contributes to predictive analytics initiatives, reporting automation, and data modeling efforts
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Engages in recurring analytics delivery while maintaining speed and quality standards
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Participates in building scalable analytical capabilities that can be reused across teams
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Supports the creation of consistent workflows to improve efficiency and reliability
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Helps integrate insights into commercial and operational planning processes
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Plays a part in strengthening customer facing model leadership through insight generation
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Collaborates with colleagues across functions to align outputs with shared organizational goals
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Engages in continuous experimentation to test new tools and quantitative methods
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Learns to quantify business impact and track measurable outcomes from analytical initiatives
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Builds dashboards, reports, and presentations tailored to varied audiences
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Develops familiarity with pharmaceutical or healthcare datasets and their commercial applications
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Operates in a fast paced environment where agility and adaptability are essential
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Gains exposure to enterprise level data platforms and modern analytics practices
Qualifications:
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Bachelor degree or equivalent in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related discipline
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Foundational knowledge of SQL for querying and managing structured datasets
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Working knowledge of Python or R for data analysis and modeling tasks
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Understanding of statistical techniques such as regression, hypothesis testing, and experiment design
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Familiarity with data visualization tools such as Power BI or Tableau
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Ability to design dashboards that communicate insights clearly and effectively
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Exposure to basic machine learning concepts including classification and clustering
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Awareness of cloud platforms such as Azure and associated data engineering practices
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Strong analytical thinking and structured problem solving ability
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Capability to gather requirements from stakeholders and translate them into data tasks
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Clear written and verbal communication skills for presenting findings
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Attention to detail when validating data accuracy and integrity
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Ability to manage turnaround times aligned with defined service level expectations
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Openness to feedback and willingness to refine analytical outputs iteratively
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Curiosity to explore emerging analytical technologies and assess their business relevance
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Team oriented mindset with readiness to collaborate across departments
Responsibilities:
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Translate local and customer level insights into practical guidance that supports strategic planning
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Prepare and deliver recurring analytics reports for stakeholders with accuracy and consistency
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Ensure adherence to agreed service levels while maintaining high standards of data quality
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Develop and maintain automated workflows that improve reporting efficiency
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Explore and test new quantitative techniques that strengthen analytical rigor
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Assist in rolling out analytics capabilities across teams to enable scalability
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Foster a mindset of measurement and continuous enhancement within the analytics function
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Integrate datasets from multiple internal and external platforms to build reliable analytical assets
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Monitor evolving trends in analytics across industries and evaluate relevance for application
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Create dashboards, written summaries, and presentation materials to communicate insights effectively
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Recommend actionable steps based on analysis and track their measurable outcomes
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Support customer facing decision models through accurate and timely data inputs
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Collaborate with technology and business teams to align outputs with enterprise objectives
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Contribute to building reusable data pipelines and structured reporting frameworks
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Participate in cross functional meetings to understand business challenges and propose data driven solutions
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Maintain documentation of methodologies, assumptions, and data sources used in analyses
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Uphold compliance, confidentiality, and ethical handling of sensitive healthcare data
Additional info:
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Hybrid working model requiring presence in office for collaboration and team engagement
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Flexible approach that balances organizational expectations with individual needs
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Encourages experimentation and rapid testing of ideas within analytics projects
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Exposure to global teams and diverse perspectives within a multinational organization
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Opportunity to contribute to healthcare solutions that impact patient lives
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Access to learning platforms, mentoring programs, and leadership development initiatives
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Performance based rewards aligned with contribution and growth
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Inclusive hiring practices that welcome applicants from varied backgrounds
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Equal opportunity employer adhering to applicable employment regulations
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Strong culture of knowledge sharing and peer coaching
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Emphasis on autonomy, allowing professionals to take ownership of their work
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Support for wellbeing through dedicated programs and employee assistance resources
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Recognition programs that celebrate innovation and collaboration
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Structured onboarding to help new joiners integrate smoothly into teams
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Encouragement to build long term career pathways within analytics and beyond
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Participation in a digitally enabled enterprise focused on modernization and efficiency
Please click here to apply.

