Sep 2022 – Jun 2023 · 9 mos · Bengaluru, Karnataka, India · On-site

• Sales and Demand Forecasting:
• Developed and implemented advanced time series forecasting models using ARIMA, Prophet, and LSTM algorithms for a Japanese luxury omnibrand curator and distributor.
• Conducted data cleaning and preprocessing techniques, including outlier detection, imputation, and feature engineering.
• Collaborated with cross-functional teams to gather insights and inputs on market trends, customer behavior, and product availability.
• Utilized statistical metrics to measure and evaluate the accuracy of the forecasting models and developed interactive dashboards and reports using Python Dash to communicate the results.
• FMP Modeling:
• Led data science team in developing a proprietary product to extract insights from financial statements, earnings call transcripts, holdings data, and news articles.
• Implemented transfer learning techniques using pre-trained models like BERT for sentiment analysis and topic modelling on earnings call transcripts.
• Utilized Power BI to analyze data from various financial statements to provide insights for investors and equity analysts.

Jun 2022 – Sep 2022 · 3 mos

Jun 2019 – Jul 2022 · 3 yrs 1 mo · Bengaluru, Karnataka, India

• Revenue Growth Management(Retail Price optimization)
• Objectives
• Develop a set of pricing guidelines by relevant channels, markets and retailers to identify
• 1.How sensitive is product to base price changes?
• 2.How will competitor’s price changes impact my brand?
• 3.What is the role of competition and strength of competitive interactions both within and outside portfolio
• 4.How effective is merchandising?
• Developed revenue forecasting model using PySpark and Python to identify price elasticity of demand for different products at Store-Week level. Conducted thorough data cleaning and preprocessing for accurate and consistent data. Utilized log-log regression model to analyze impact of external variables on revenue growth.
• Marketing Mix Modeling.
• Objective: Understand the key drivers of Brand sales and to identify which marketing channels delivered the highest (and lowest) ROI among TV, Print, Digital etc so that optimal allocation of marketing spends can be done for profitable future growth for Brand
• Developed market mix models using Python to analyze impact of marketing levers on sales performance for a retail company. Preprocessed and transformed data to account for seasonality and trends, and incorporated adstock and adbudget parameters. Utilized linear regression models to estimate price elasticity of demand for different products at store-week level. Incorporated advanced feature engineering techniques, such as interaction terms, lags, and dynamic effects, to improve predictive power.
• Market Structure Automation:
• Implemented switch matrix and chi-square test to check for significant difference in brand switching between two groups. Conducted data analysis to identify patterns in brand switching behavior and factors influencing brand loyalty. Provided insights into consumer preferences and purchasing behavior to optimize marketing and advertising strategies.

Dec 2013 – Jun 2019 · 5 yrs 6 mos · Bengaluru

• Worked with telecom clients like Bell Canada and Hutchinson UK.
• Responsibilities included primary and secondary research, to analyze and synthesize research findings to develop valuable insights and strategic recommendations. Technology Stack- Python
• Designed and created client-ready presentations in Microsoft, Powerpoint, Word, and Excel