I'm Shuchismita Mallick
I'm a passionate Data Scientist with 3 years of experience in transforming complex data into actionable insights. My journey in data science has been driven by a deep curiosity for understanding patterns and solving real-world problems. I specialize in machine learning, predictive modeling, and data-driven decision making, with a strong focus on developing end-to-end solutions that drive business value.
Programming
Developing efficient data processing solutions with Python and SQL.
Analytics
Transforming raw data into business insights. Expertise in E-Commerce & Retail-cpg domain. Learning Fintech and Insurance domain.
Machine Learning
Experienced in Machine Learning techniques including Regression, Classification, Deep Learning, Feature Engineering, and Model Evaluation.
Tools & Platforms
Skilled in using Tools & Platforms such as Azure ML Studio, Databricks, AI Foundry, MLflow, and SSMS.
Projects
Impactful Projects Delivered at Work in Fractal Analytics
Customer Journey Optimization – Lead Scoring Model
Designed and deployed a machine learning-based lead scoring model on Databricks for a global FMCG enterprise across South Africa, Indonesia, and Egypt. Optimized customer journey touchpoints by identifying high-conversion prospects and enabling data-driven marketing strategies across multiple emerging markets.
Advanced Time Series Sales Forecasting
Enhanced univariate and multivariate time series models to forecast dollar sales, equivalent sales, and unit sales for a multinational consumer goods leader in North America. Improved forecast accuracy through advanced statistical modeling and feature optimization to support demand planning and revenue strategy.
Impactful Projects Delivered at Work in Enqurious
Autonomous Agentic AI Solution for Healthcare
Developed an autonomous agentic AI solution for healthcare that automates data retrieval and generates real-time insights to enhance decision-making and operational efficiency for hospital staff.
Predicting Optimal Channel for New Product Launch
Built predictive models to identify the most effective marketing channels for launching new products, improving launch success rates.
POC: AI Agent for Content Inventory Exploration
Developed a proof-of-concept AI agent to help the Content Development Team explore and analyze content inventory efficiently.
Dynamic Pricing for Optimizing Pricing Strategy
Implemented dynamic pricing models to optimize product pricing strategies, increasing revenue and market competitiveness.
POC: AI Agent for Reporting to Client
Created a proof-of-concept AI agent for the Ops Team to automate and streamline client reporting processes.
Market Mix Modeling for Optimized Budget Allocation
Developed a market mix model to optimize marketing budget allocation across channels, maximizing ROI and efficiency.
Passion Projects & Personal Growth
Market Mix Modeling
Built a market mix model to analyze and optimize marketing spend across multiple channels for improved ROI.
Water Profiling Score Project
Developed a scoring system to profile water quality using data analysis and machine learning techniques.
Book Recommendation (RAG Chain)
Implemented a book recommendation system using Retrieval-Augmented Generation (RAG) and NLP techniques.
Customer Churn Prediction
Created predictive models to identify customers at risk of churning, enabling targeted retention strategies.
Customer Purchase Behavior
Analyzed and modeled customer purchase patterns to uncover insights and drive business growth.
Experience
Data Scientist Fractal Analytics
- Customer Journey Optimization – Lead Scoring Model:Designed a lead scoring model in Databricks for a Fortune 500 global FMCG company across South Africa, Indonesia, and Egypt.
- Improved univariate and multivariate time series forecasting models to predict dollar sales, equivalent sales, and unit sales for a Fortune 500 global FMCG enterprise in North America.
Data Scientist Enquorious
- Led the creation and execution of data science projects, constructing proofs of concept (POC) tailored for EdTech solutions and mentoring aspiring decision scientists.
- Conducted data analysis and used statistical models and machine learning techniques to evaluate channel effectiveness and develop strategies for redistributing budgets, maximizing sales, and profitability.
- Developed and deployed machine learning models to Databricks endpoints for real-time customer risk prediction.
- Prepared end-to-end solutions in Azure ML Studio, focusing on Market-mix modeling, dynamic pricing for price optimization, and optimal channel prediction for new product launches.
- Developed Agentic-RAG Chat-bot utilizing AzureAIFoundry,AI Search, connecting with Unity Catalog in the Health Care domain based on Non-clinical Metrics, whose dataset was curated by me
Data Analyst Enquorious
- Created multiple data analysis projects in Python, SQL, and Power BI across various domains to address the company's needs.
- Conducted live sessions with clients to deliver hands-on learning experiences, enabling them to enhance their skills effectively.
- Designed and implemented deep learning models with a computer vision pipeline using CNNs to classify traffic signs from image datasets, advancing automated driving systems.
- Implemented uplift modeling techniques to predict the incremental impact of marketing strategies, enabling personalized campaigns by identifying customers likely to respond positively.
Data Analyst Intern Enquorious
- Conducted live sessions with clients by creating hands-on projects in Python and MySQL, fostering an interactive and practical learning experience.
- Designed scenarios based on e-commerce and sports domains to enhance client understanding of data processing and wrangling techniques.