This is contract to hire opportunity with 3+ years of experience onwards., If you are interested pls share your resume to karthik.ravichandran@hays.com.au with below details.
- Over all exp;
- Relevant exp;
- Current location;
- CCTC;
- ECTC;
- Notice period;
Job Description
Essential for the role
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).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 backgroundML a plusExperience 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 (3–7 yrs)
The ideal candidate is a data-driven analytics professional with 3–7 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.