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Tiger Analytics
AI & Analytics for today’s business challenges.
Machine Learning • Predictive Analytics • Forecasting • Optimization • Natural Language Processing
1001 - 5000
Lead Data Scientist - Marketing Mix Modeling
August 3
Tiger Analytics
AI & Analytics for today’s business challenges.
Machine Learning • Predictive Analytics • Forecasting • Optimization • Natural Language Processing
1001 - 5000
Description
• Work on the latest applications of data science to solve business problems in the Marketing analytics team of the Retail and CPG space. • Effectively communicate the analytics approach and how it will meet and address objectives to business partners. • Develop clear, concise, actionable solutions and recommendations for Client's business needs • Work with client analytics team to carry out Market Mix Modelling / ROI analytics • Undertake hands on work on data analytics, model development and testing and preparing the data files for visualization platforms • Undertake business analysis on the data and provide insights • Coordinate with decision makers to translate business questions into a verifiable hypothesis and data models • Work hands-on across various analytics problems and provide thought leadership on problems • Interact with onsite team as well as client on daily/weekly basis to gather requirements/ provide updates • Stay connected with external sources of ideas through conferences and community engagements. • Support demands from regulators, investor relations, etc., to develop innovative solutions to meet objectives utilizing cutting-edge techniques and tools.
Requirements
• 8+ years of experience of working with CPG clients or in a CPG company • Graduation or Post graduation in Statistics, Mathematics, Management etc. • Must have worked with Marketing analytics teams and understand Market Mix Modeling (MMM) work comprehensively. Must have led multiple projects on MMM analytics • Experience in pricing and promotion analytics is a plus • Must have experience with Databricks • Implemented Bayesian regression on python. Exposure to libraries like numpy, pandas, sklearn, pymc3 • Hands on experience in PowerPoint / Excel is a must • Strong logical, analytical, and problem-solving skills • Adept at report writing and presenting findings • Excellent verbal and written communication skills
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