Manager - Business Analytics

Job Overview

Sales, Operations, Finance & Supply Chain Teams

• Master's in Statistics, Information Systems, Computer Sciences, Mathematics, Operational Research or any quantitative domain with MBA degree preferred, Engineering Pass out.
• Analytics Tools - Python, SQL, MS Excel (Including VBA)
• Predictive Analytics - Machine Learning Algorithms, Logistics & Linear Regression, Decision Tree, Clustering.
• Exploratory Data Analysis - Data Preparation, Data Exploration, and Data Visualization.
• Expertise - Descriptive, Diagnostic, Predictive, and Prescriptive Analytics.
  

• Manager Analytics will be responsible for building and implementing data solutions to drive analytics reports.
• Assess current tools and enhance to improve flexibility and sustainability.
• Convert existing Python generated excel reports into one master data feed to be utilized in dashboards to be built in visualization tool.
• Establish new data gathering and analysis techniques within the organization.
• Drive data based decision making by providing actionable insights from customer behaviour and engagement across various touch points.
• Building and implementing next generation predictive models leveraging traditional and non traditional data.
• Successfully conceptualize, develop and deploy advanced analytics solutions in a high performing environment through data augmentation, value extraction and monetization
• In addition, the resource will be responsible for evaluating multiple machine learning and regression techniques for specific use cases.
  

• Must have coding experience in Python, advanced excel knowledge including VBA
• Must have experience working with Cloud like Azure, AWS or GCP
• He/she will interact and at times work with external partners in the industry to ensure that they remain abreast with the knowledge in pharma industry especially in analytics domain.
• Ability to communicate quantitative and technical concepts to non-technical audiences
• Excellent written and verbal communication skills
• Strong understanding of the interplay between technology, business & data
• Excellent knowledge of Pharma/Consumer goods domain to identify analytical use cases