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AstraZeneca

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4.1

based on 829 Reviews

Video summary

132 AstraZeneca Jobs

Senior Data Analyst

AstraZeneca India Pvt. Ltd

4.1

based on 829 Reviews

5-10 years

Chennai

1 vacancy

Senior Data Analyst

AstraZeneca

posted 15d ago

Job Role Insights

Flexible timing

Key skills for the job

Pharmacy Data Analysis SQL Recruitment Analytical Chemistry MS Office

+ 4 more

Job Description

Job Title: Senior Data Analyst

Career level - D1

Introduction to role

You will be responsible for providing analytical expertise to the Commercial Organization, driving strategic and operational excellence. This is a hands-on analytical role and as a proactive internal consultant to a specific brand team, the Brand Analytics Senior Analyst will support and design commercial solutions, enabling data-driven decisions that are based on rigorous analysis and best available information. A high level of proficiency in syndicated and custom, primary and secondary data, for both predictive and prescriptive analytics is required. The Brand Analytics Senior Analyst will coordinate the understanding of various datasets, design and implement analytical solutions in support of Business Opportunities, Customer Segmentation & Targeting, HCP & Patient Opportunity Identification, Return-On-Investment analytics, Patient & Prospective Analytics, Smart Business Experiments (Test & Learn), Market Simulation & Patient flow modelling among other business critical analyses. This role works closely with Marketing, Medical, Market Access, Sales, Forecasting, and other Commercial Operations business partners.

In addition to strong analytical skills, you should have excellent communication skills with a demonstrated track record of effective business partnership as demonstrated by material business impact and influencing.

Accountabilities

Develop a deep understanding of internal customers data and analytical needs focusing on the customer-facing model leadership.
Champion the use of local customer insight in strategic and resourcing decisions across the business.
Collaborate with the US Sales Force Operations to ensure success of key business processes and coordination on joint initiatives.
Identify and prioritize enhancements and new analytic capabilities. Can lead the development, deployment, and embedding of such capabilities across the organization.
Instill a culture of continuous improvement, testing, and deployment of new capabilities for the business.
Develop innovative analytical practices to create and sustain competitive advantage.
Access appropriate information via a variety of tools and sources.
Summarize and present findings through various communication channels.
Apply deeper technical skills and knowledge that is shared across the functional area (e.g., deep knowledge of key data sets, modeling capabilities, etc.).
Demonstrate a high level of understanding of the points of integration of our work and that of our colleagues.
Monitor the external environment to stay up to date on leading analytic capabilities, both within and outside of pharma, which can be applied within the organization.

Essential Skills/Experience

Quantitative Bachelor s degree from an accredited college or university is required in one of the following or related fields: Engineering, Operations Research, Management Science, Economics, Statistics, Applied Math, Computer Science or Data Science. An advanced degree is preferred (Master s, MBA or PhD).
2+ years of experience in Pharmaceutical / Biotech / Healthcare analytics or secondary data analysis.
5+ years of experience in application of advanced methods and statistical procedures on large and disparate datasets.
4+ years of recent experience and proficiency with PySpark, Python, R, SQL.
Working knowledge on platforms like DataBricks.
Working knowledge of data visualization - PowerBI, MicroStrategy, Tableau, Qlikview, D3js or similar tools is a plus.

- Experience in MS Office products - Excel and PowerPoint skills required.

Proficiency in manipulating and extracting insights from large longitudinal data sources, such as Claims, EMR and other patient level data sets.
Experience with IQVIA data sets.
Ability to derive, summarize and communicate insights from analyses.
Organization and time management skills.
Expertise in managing and analyzing a range of large, secondary transactional databases is required.
Statistical analysis and modelling background.
ML a plus.
Statistical Analysis & Modelling: Design of Experiments, Time Series, Regression, Applied Econometrics and Bayesian methods.
Data Mining, Predictive Modelling & Machine Learning algorithms.
Optimization & Simulation.

Desirable Skills/Experience

Strong leadership and interpersonal skills with demonstrated ability to work collaboratively with a significant number of business leaders and cross-functional business partners.
Strong communication and influencing skills with demonstrated ability to develop and effectively present succinct, compelling reviews of independently developed analyses infused with insight and business implications/actions to be considered.
Strategic and critical thinking with the ability to engage, build and maintain credibility with Commercial Leadership Team.
Strong organizational skills and time management; ability to manage diverse range of simultaneous projects.
Knowledge of AZ brand and Science (Oncology in particular).
Experience using Big Data is a plus. Exposure to SPARK is desirable.
Excellent Analytical, Problem Solving ability. Should be able to grasp new concepts quickly.

At AstraZeneca, our work has a direct impact on patients by transforming our ability to develop life-changing medicines. We empower the business to perform at its peak by combining cutting-edge science with leading digital technology platforms and data. Join us at a crucial stage of our journey in becoming a digital and data-led enterprise. Make the impossible possible by building partnerships and ecosystems, creating new ways of working and driving scale and speed to deliver exponential growth.

Date Posted

14-Feb-2025

Closing Date

27-Feb-2025

Employment Type: Full Time, Permanent

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