Data Analyst

This is contract to hire opportunity with 3+ years of experience onwards., If you are interested pls share your resume to with below details.

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Job Description

Essential for the role

• Quantitative bachelors 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 (Masters, MBA or PhD).
• 3+ years of experience in application of advanced methods and statistical procedures on large and disparate datasets.
• Statistical Analysis & Modelling: Design of Experiments, Time Series, Regression, Applied Econometrics and Bayesian methods.
• Data Mining, Predictive Modelling & Machine Learning algorithms.
• Optimization & Simulation.
• 3+ years of recent experience and proficiency with PySpark, Python, R, SQL.
• Working knowledge of data visualization PowerBI, MicroStrategy, Tableau, Qlikview, D3js or similar tools.
• Working knowledge on platforms like DataBricks.
• Experience in MS Office products - Excel and PowerPoint skills required.
• Expertise in managing and analyzing a range of large, transactional databases is required.
• Statistical analysis and modelling background
• ML a plus
• Experience with IQVIA data sets.
• Ability to derive, summarize and communicate insights from analyses.
• Organization and time management skills.

Desirable

• 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.
• Should have Excellent Analytical, Problem-Solving ability. Should be able to grasp new concepts quickly

Ideal Candidate Summary Brand Analytics / Data Analyst (37 yrs)

• The ideal candidate is a data-driven analytics professional with 37 years of hands-on experience in advanced statistical modelling, predictive analytics, data mining, and machine learning , preferably within the pharma or commercial analytics domain. They should have strong expertise in Python, PySpark, R, SQL , and experience working with large, complex datasets, especially IQVIA or other healthcare datasets.
• They bring a strong foundation in statistical methods (regression, time series, DOE, Bayesian approaches), along with experience in optimization, simulation , and building predictive/prescriptive models. The candidate is comfortable working on platforms like Databricks and creating impactful visualizations using PowerBI, Tableau, Qlik , or similar tools.
• They function as a proactive internal consultant , partnering closely with Marketing, Sales, Medical, Market Access, and Commercial teams to drive customer segmentation, targeting, ROI analysis, forecasting support, HCP/patient analytics, resource allocation , and market simulations . They excel at converting complex analysis into clear business insights and influencing stakeholders through strong storytelling and presentation skills.
• The ideal candidate demonstrates strategic thinking , excellent communication, strong business acumen, and the ability to manage multiple analytical projects simultaneously. Experience in pharma/oncology , exposure to big data technologies (Spark) , and knowledge of US commercial datasets is a strong plus. They stay current with new analytical techniques, champion continuous improvement, and contribute to elevating analytic capabilities across the organization.