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Metro locations and generalist ML/data role increase candidate competition despite modest employer brand.
Pharma-focused requirements increase domain specificity, reducing cross-industry transferability.
Broad tech stack and pharma-domain expectations without explicit years creates moderate shortlisting strictness.
Lead end-to-end implementation of data science projects from scope definition to delivery.
Develop and apply advanced statistical, econometric, and optimization models to solve real-world business problems in the pharma domain.
Collaborate with internal and external stakeholders to understand requirements and deliver timely, high-quality data analysis and modeling solutions.
Proven experience in data analysis and model development using Python, R, or SAS.
Experience with Pyspark, SQL, and Big Query tools.
Strong quantitative and problem-solving skills with ability to build models and simulation tools from scratch.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in applying advanced analytics specifically within the pharmaceutical domain.
Able to manage projects effectively ensuring adherence to timelines and quality standards.
Capable of working closely with diverse stakeholders, both internal teams and external clients, to translate business needs into analytical solutions.