Manoj Ram Mopati

Results-driven Data Scientist with hands-on experience in data modelling, statistical analysis and predictive modelling across retail, consumer products and debt recovery domains using large-scale business data. Skilled in SQL, Python, R, PySpark, MLOps and Power BI, with experience identifying sales trends, building scalable data solutions and machine learning models, generating insights and translating complex data into clear, actionable business recommendations. A focused, adaptable self-starter with excellent written and verbal communication skills, able to work independently and respond quickly to evolving business needs.

DATA SCIENTIST at INFOSYS LIMITED (2023-01 – 2025-05)

• Processed and analysed large volumes of retail sales and marketing data using Python, R, PySpark and SQL performing data cleaning, transformation, feature engineering, and modelling dataset preparation.
• Developed MMM-style sales-driver models using log-log regression to measure the impact of price, promotions, feature/display activity, seasonality, holidays, stock-up effects, and competitor actions on weekly sales performance.
• Translated model outputs into actionable business insights, including sales attribution, promotional lift, ROI estimates, and driver contribution waterfalls to support marketing and trade spend optimisation.
• Designed and supported end-to-end data science workflows using Azure Databricks, Azure Data Factory, Azure Delta Lake, Azure SQL Database, and Azure DevOps and MLOps for scalable data processing and model output deployment.
• Developed a Power BI sales portfolio analytics and reporting platform for the billion-dollar US confectionery market, enabling SRM and trade teams to monitor sales performance, promotion effectiveness, and revenue management KPIs.
• Developed trade promotion optimisation tools to help retail business users evaluate offer strategies, optimize promotional calendars, and improve profit-oriented decision-making across key retail channels.
• Collaborated with cross-functional teams of data scientists, data engineers, Product Owners, and business analysts to create ETL and CI/CD pipelines and machine learning models.

ASSOCIATE DATA SCIENTIST at INFOSYS LTD (2022-02 – 2023-01)

• Built an RFM model using Python, R, Machine Learning, SQL, and Power BI and Microsoft Fabric to segment 200K+ customers based on payment behaviour and outstanding debt, identifying high, medium, and low-risk profiles.
• Enabled targeted debt recovery strategies by aligning resource allocation with customer risk tiers, increasing recovery rates by 18%, and reducing average recovery time by 12 days.
• Created an executive-level Power BI and Microsoft Fabric dashboards visualizing customer segments, debt ageing, total exposure, and recovery status, supporting data-driven decisions at the C-suite level.
• Developed and delivered end-to-end data solutions using SQL, Power BI and Microsoft Fabric tailored to stakeholder requirements while proactively identifying opportunities for deeper insight.
• Experienced in writing complex SQL queries and Python scripts for large-scale data cleansing, transformation, and analysis to drive actionable business outcomes.

Master of Science in Data Science – Coventry University (2025-05 – 2026-05)

Bachelor of Technology in Mechanical Engineering – Visvodaya Engineering College - Kavali (2017-07 – 2021-06)