Self-driven professional with 6+ years of experience in data science, Machine Learning and Artificial Intelligence for Retail, CPG, and Marketing. An expert in organizational skills, mentorship, leading, planning and exe…
Self-driven professional with 6+ years of experience in data science, Machine Learning and Artificial Intelligence for Retail, CPG, and Marketing. An expert in organizational skills, mentorship, leading, planning and executing products, and developing algorithms. Innovative thinker who likes to solve complex problems using statistical techniques, ML, AI and optimization with tools including Python, SQL and MS Power BI
● Conducted and oversaw research as part of Product innovation and Development Team to study, assess, and support NIQ’s current products, improve client satisfaction and build new functionalities.
● Created a patent-pending Clustering-based Machine Learning Algorithm for Retail intelligence product to detect Bulk Sales for 10+ FMCG categories using NumPy, Pandas, Scikit-learn, and seaborn.
● Developed a regression-based algorithm to correctly estimate annual turnover for non-participating stores in 8 countries, helping the company acquire $14 Million in client contracts.
● Conceptualized, developed, and supported deployment of model to predict category-based stock values from sales value for 1 million+ stores in 10+ countries.
● Pitched and created 20+ dashboards with the Product Team using Power BI to present Performance KPIs to 2 Major Clients in Soft Drink Category.
● Collaborated with senior leadership and cross-functional teams to play a pivotal role in creation and establishment Roadmaps for 5+ projects using agile methodology.
Conducted and oversaw research as part of Product innovation and Development Team to study, assess, and support NIQ’s current products, improve client satisfaction and build new functionalities.
Created a patent-pending Clustering-based Machine Learning Algorithm for Retail intelligence product to detect Bulk Sales for 10+ FMCG categories using NumPy, Pandas, Scikit-learn, and seaborn.
Developed a regression-based algorithm to correctly estimate annual turnover for non-participating stores in 8 countries, helping the company acquire $14 Million in client contracts.
Conceptualized, developed, and supported deployment of model to predict category-based stock values from sales value for 1 million+ stores in 10+ countries.
Pitched and created 20+ dashboards with the Product Team using Power BI to present Performance KPIs to 2 Major Clients in Soft Drink Category.
Collaborated with senior leadership and cross-functional teams to play a pivotal role in creation and establishment Roadmaps for 5+ projects using agile methodology.
Led and trained a team of 3 members to work in collaboration with Product, Technology, and Leadership.
Utilized statistical models and predictive analytics to assess customer behavior, enabling proactive identification of potential opportunities for product and service promotions.
Conducted A/B testing on various marketing campaigns, analyzing results to enhance overall campaign performance by 18%.
Created and delivered comprehensive reports using Tableau to senior management, summarizing findings and recommending actionable insights to drive business growth.
Formulated and executed the process of developing a content curation engine which maps data blocks extracted from more than 300 User Manuals to Taxonomy Elements.
Scoped, Developed, and deployed DS / ML models to classify text blocks to taxonomy labels to increase accuracy by ~24.5%.
Developed clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
Utilized data analytics tools and techniques to extract actionable insights from customer behavior, improving user experience and driving product/service optimization.
Developed and maintained key performance indicators (KPIs) dashboards, providing stakeholders with real-time data to support data-driven decision-making.
Guided 4 upcoming convenience store chains establish themselves by conducting sales, inventory, and customer data analysis.
Led targeted marketing campaigns for 5 clients through comprehensive analysis of customer demographics and behavior.
Streamlined internal processes resulting in a 50% reduction in turnaround time for project deliverables and created production ready scripts to enable application development by adding Data Science and ML functionalities.
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