Advanced AI-Driven Retail Merchandising Expert

@avinashdubeyg209

Notice you want to leverage Generative AI in retail merchandising and pricing. Recently developed a forecasting and optimization model for an e-commerce firm using GPT-3, enhancing their price elasticity predictions by 20%. What's your primary goal—boosting sales, optimizing inventory, or something else? Can start today and discuss how we can implement scalable AI solutions tailored to your needs. Let me know how you'd like to proceed, happy to share a quick plan.

@shakilan4

Hi, I am an experienced Data Scientist with expertise in AI, Generative AI, and retail analytics, skilled in building scalable forecasting, pricing, and optimization models using LSTM, Transformers, and modern ML tools. I can deliver end-to-end solutions with deployment, CI/CD, and seamless API integration. Best regards, Shakila Naz

@chiragardeshna

Hi there, Strong alignment with this role comes from building AI-driven systems for forecasting, optimization, and intelligent automation across data-intensive applications. Clear understanding of developing demand forecasting, price optimization, and assortment planning using ML/DL models, along with LLM-based automation and analytics. Hands-on expertise with Python, TensorFlow/PyTorch, and LLM frameworks ensures scalable pipelines, model lifecycle management, and API-based integrations. Risk is minimized through robust validation, monitoring, retraining strategies, and CI/CD pipelines for reliable production deployment. Available to start immediately happy to discuss approach or share relevant AI project experience. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@amaank66

You’re not just looking for a data scientist—you need someone who can turn advanced modeling into real business impact at scale across merchandising, pricing, and operations. I work at the intersection of forecasting, optimization, and AI systems, with a focus on production-ready pipelines—not just experiments. Forecasting & demand intelligence • Hierarchical + multivariate forecasting (SKU → store → region) • Handling cold-start, sparse data, and cross-level reconciliation • LSTM/Transformer models where they add value over classical methods Pricing & assortment optimization • Price elasticity modeling + demand response curves • Optimization engines for assortment planning and inventory allocation • Scenario simulation to guide merchandising decisions Generative AI & LLM integration • LLM-powered agents for analytics automation, reporting, and decision support • LangChain/OpenAI pipelines for structured insights from large datasets MLOps & scalability • End-to-end pipelines (training → deployment → monitoring → retraining) • CI/CD integration, experiment tracking, and performance evaluation • API-first architecture for seamless integration with existing systems I’ve worked on similar data-driven systems where the goal was not just accuracy, but actionable decisions that improve revenue, margins, and inventory efficiency. Best regards, Amaan Khan L. (CUBEMOONS PVT.)

@abdf2010

Hello. I came across your project, Advanced AI-Driven Retail Merchandising Expert and it aligns well with my background. I have hands-on experience with Data Science, Deep Learning, Predictive Analytics that's directly relevant here. Feel free to reach out if you have questions.

@vladislavg00000

Hello, With a background in full stack engineering and a specific focus on AI, your innovative retail project is right up my alley. I've spent the past 9+ years using cutting-edge technologies to build scalable solutions that align with business goals - exactly what you're looking for. From conceiving complex ideas to delivering user-friendly applications, I've garnered deep skillsets in advanced machine learning models, such as LSTMs and Transformer-based models just to name a few. Demand forecasting, price elasticity modeling, optimizing inventory - they're all part of my usual retinue. My knowledge extends to dealing with the most sophisticated forecasting challenges such as those that arise from cold-start problems or difficulties in balancing successive levels within the hierarchy - all while working with massive datasets.I pride myself on using scalable solutions such as Generative AI techniques to improve operations and maximize customer value. Effectively managing the lifecycle of complex ML projects including monitoring, retraining and performance evaluation is ingrained in my professional DNA. It's a task i approach with laser-like focus.I have experience in maintaining CI/CD pipelines for reliable and scalable deployment of data science solutions. In addition to leveraging modern machine learning frameworks and tools like TensorFlow ,PyTorch etc . Let me bring my skills to bear on your project while you concentrate on ot Thanks!

@Farhan8809

Hi there, and warm greetings. I’m Farhan Shabbir, a data scientist with strong expertise in AI, Generative AI, and predictive analytics. I understand you need advanced, scalable solutions for retail merchandising, pricing, and forecasting. ◉ AI/GenAI-driven models for merchandising and pricing optimization ◉ Demand forecasting using multivariate and hierarchical models ◉ Price elasticity and assortment optimization strategies ◉ Inventory allocation and replenishment modeling ◉ Scalable ML pipelines for real-time and batch processing I focus on building intelligent, data-driven systems that improve decision-making and business performance. My approach combines strong modeling with practical deployment to ensure real impact. Communication is clear, and solutions are delivered efficiently. Risk-Free Guarantee → No upfront payment. Pay only when satisfied. Let’s connect and build something great.

@kamran2012

Hi there, I will build your retail merchandising AI system — demand forecasting with hierarchical reconciliation, price elasticity modeling, and assortment optimization powered by ML and GenAI. For demand forecasting, I will implement a Transformer-based architecture with cross-level reconciliation that handles cold-start SKUs by transferring learned embeddings from similar product clusters. This approach outperforms traditional LSTM pipelines on sparse retail data while scaling efficiently across large catalogs. Questions: 1) What is the current data infrastructure — are forecasting models expected to run on cloud (AWS/GCP) or on-premise? 2) Do you have historical transaction data ready, or will data pipeline development be part of the initial scope? Looking forward to discussing further. Best regards, Kamran

@vincentm062

Hello! Your project aligns perfectly with my experience building AI-driven retail analytics systems, combining forecasting, optimization, and Generative AI to drive real business impact. ⚡ The key success factor is integrating forecasting, pricing, and optimization into one scalable pipeline—not isolated models, but a cohesive decision engine. ⚡ My experience includes: Demand forecasting (hierarchical, multivariate, long-range) using LSTM & Transformer models Price elasticity modeling and assortment optimization Building LLM-powered analytics workflows for automation and insights Handling cold-start problems and large-scale datasets Deploying ML systems with CI/CD, monitoring, and retraining pipelines ⚡ My approach: Design scalable data pipelines + feature engineering Build forecasting + optimization models aligned with business KPIs Integrate Generative AI/agents for decision support and automation Deploy via APIs with full lifecycle management (tracking, monitoring) ? Stack: Python, PyTorch/TensorFlow, LLMs, APIs, MLOps ⏱ Availability: Immediate, long-term collaboration I focus on production-grade AI systems that deliver measurable ROI, not just experiments. Let's have a quick call to discuss more details. Thanks.

@CANWS

Dear Hiring Manager, I am excited to apply for the Data Scientist position focused on retail merchandising and pricing analytics. With deep expertise in AI, Generative AI, and advanced machine learning, I specialize in building scalable solutions that drive demand forecasting, assortment optimization, and intelligent pricing strategies. In previous roles, I have designed and deployed multivariate and hierarchical forecasting models (including LSTM and Transformer architectures) to solve complex challenges such as cold-start problems, cross-level reconciliation, and large-scale multi-echelon predictions. I have also developed AI/ML-driven assortment planning algorithms using customer behavior data and implemented price elasticity modeling that significantly improved revenue and inventory efficiency. I am highly proficient with TensorFlow, PyTorch, OpenAI, and LangChain, and have extensive experience leveraging LLMs and agent-based systems for analytics automation. I manage the full ML lifecycle — from experimentation and monitoring to CI/CD pipelines — ensuring reliable production deployment and seamless integration via APIs. I am eager to bring innovative, data-driven solutions to your retail initiatives and help maximize customer value through optimization models. I would welcome the opportunity to discuss how my background can contribute to your team’s goals. Thank you for your consideration. Best regards, Mayank

@Pieter21

As an experienced AI developer and skilled data scientist, I possess the exact skills you're seeking for this demanding and exciting role. My deep understanding of AI and Generative AI techniques would be a valuable asset in driving innovation in retail merchandising and pricing analytics. Leveraging my expertise, I am well-versed in building highly scalable solutions ranging from demand forecasting to price elasticity modeling. My dedication for implementing the latest technologies such as Large Language Models (LLMs), Generative AI, and agent-based systems is well-aligned with the project's objective of enhancing analytics and automation capabilities. Furthermore, my proficiency in utilizing machine learning frameworks, tools like TensorFlow, PyTorch, OpenAI, and LangChain would ensure a seamless integration of these advanced models with your existing applications. In terms of scaling predictions, developing multivariate and hierarchical models to address complex challenges is a skill that I have exercised successfully numerous times. I am confident that my experience in managing the entire machine learning lifecycle while maintaining high-performance levels will prove invaluable to your retail merchandising project. Allow me to leverage my skills and passion to exceed your expectations on this initiative.

@markop815

Hey! This is exactly the kind of end-to-end AI/ML work I specialize in—combining forecasting, optimization, and GenAI into scalable systems. I work with Python (PyTorch, TensorFlow), LLMs (OpenAI/Claude), and pipelines using Airflow + CI/CD. Recently, I built a retail forecasting system handling multi-level demand (SKU → region), where cold-start SKUs were a major issue. I solved it using hierarchical models + embeddings from product metadata, improving forecast accuracy and enabling better inventory allocation. For your project, I can design demand forecasting (LSTM/Transformer), price elasticity models, and assortment optimization, then layer in GenAI/agent workflows for insights and automation. I also handle deployment, monitoring, and retraining pipelines. Happy to discuss architecture and start with a focused module. Thanks!

@harryv33

✨ Hi, there ✨ Your project is a strong match for my background in AI, forecasting, optimization, and production-grade ML systems. I can help build scalable retail solutions for demand forecasting, price elasticity, assortment optimization, and inventory allocation, while also leveraging LLMs/GenAI for smarter analytics and automation. I’m experienced with: ♦️ Python, PyTorch, TensorFlow, Transformers ♦️ Retail forecasting (hierarchical/multivariate, cold-start, reconciliation) ♦️ Optimization models for pricing, replenishment, and assortment ♦️ LLM/GenAI workflows using OpenAI + LangChain ♦️ MLOps / CI-CD / API deployment for reliable production systems I focus on solutions that are not just accurate, but scalable, explainable, and business-impact driven. I’d be happy to discuss your data, current stack, and propose a practical roadmap. ✌️ Best regards ✌️

@alizain721

Deliver production-grade AI for retail merchandising: long-range, multi-echelon demand forecasting, price-elasticity modeling, assortment optimization, and automated replenishment — delivered as deployable models + CI/CD + monitoring. In scope: hierarchical/multi-step forecasts, cold-start handling, LLM-assisted feature engineering, optimization for allocation/pricing, API integration. Out of scope: front-end UI redesign or POS system changes. Biggest failure modes: inconsistent SKU/category hierarchies, unreconciled forecasts across levels, and absent drift detection. Sharp insight: reconciling forecasts must be part of the model and loss function, not a post-processing step. Training with hierarchical loss (or probabilistic reconciliation like MinT-style methods) and using SKU embeddings from LLMs for cold-starts prevents downstream allocation and pricing optimizers from applying broken inputs. Relevant proof: core skills match the brief — Transformer models, LSTM, Generative AI/LLMs, TensorFlow/PyTorch, LangChain and production ML lifecycle (CI/CD, monitoring). Approach (brief): ingest POS/inventory/promotions into a feature store → train ensemble (hierarchical Transformer + LSTM) with reconciled loss → use LLM embeddings for new SKUs → optimization via MILP for allocation/pricing → package in Docker, deploy on K8s with MLflow + drift alerts. Quick question to scope next step: do you have a canonical SKU → category → node hierarchy and a daily transaction feed (roughly how many SKUs and stores)?

@chechiko

Hi! Looking at your requirements, this is a highly ambitious, enterprise-grade roadmap. As a Data Science Engineer specializing in AI and Python automation, I know that combining hierarchical demand forecasting with GenAI agents requires a robust, scalable foundation before moving into full CI/CD deployment. Given the initial budget, I propose we start with Phase 1: A Proof of Concept (PoC) to validate the core logic before scaling. My Technical Approach for Phase 1 (Choose one to start): Option A (Predictive Engine): I will build the baseline demand forecasting model using PyTorch (LSTM/Transformers). To address your specific mention of the "cold-start" problem, I will implement metadata-based feature engineering to predict demand for new SKUs without historical data. Option B (GenAI Merchandising Agent): I will develop a reasoning agent using LangChain and OpenAI. This agent will ingest your structured retail data to automate merchandising insights and price elasticity recommendations. Deliverables for this phase: Clean, modular Python code (PEP8). A functional MVP (either the forecasting model or the GenAI agent). A deployment-ready Dockerized API to ensure future CI/CD compatibility. Let me know which module is your highest priority right now, and we can lock in the architecture. Kind regards, Benjamín

@revoh7

I am a perfect fit for your project because the goal is to create a seamless, user‑friendly, and professionally built solution with strong attention to detail. I focus on results that are functional, efficient, and well designed. I offer experience in web design and development, software architecture, APIs, AI development, UX, and online marketing. While I am new to freelancer, I have tons of experience and have done other projects off site. I would love to chat more about your project! Regards, Revo

@AsserNasser22

I will implement a transformer-based predictive model for dynamic retail product recommendations using generative AI. The system will process historical sales data to forecast demand patterns and generate optimized merchandising strategies. I'll integrate large language models to analyze customer feedback and refine inventory allocation. What specific metrics do you prioritize for demand forecasting accuracy? I provide free technical revisions after delivery.

@shymaa78

Hello ? I’m excited to apply for this opportunity as a Data Scientist specializing in AI and Generative AI, with experience in building scalable, advanced analytics solutions for forecasting, pricing, and optimization. ✨ **Why I’m a strong fit:** * Proven experience in developing and deploying advanced machine learning models to support data-driven decision-making * Building demand forecasting systems using multivariate and hierarchical models, handling challenges like cold start and large-scale data * Experience in price elasticity modeling, assortment optimization, and inventory allocation/replenishment * Applying deep learning models such as LSTM and Transformers in e-commerce and customer behavior analysis ? **Generative AI expertise:** * Leveraging Large Language Models (LLMs) and agent-based systems to enhance analytics and automation * Building intelligent solutions that combine predictive and generative AI for real business impact I’m eager to contribute to innovative retail analytics solutions and drive measurable impact through AI. Looking forward to discussing this further ?

@nathanholmes

We’ve just completed a project enhancing demand forecasting accuracy by implementing hierarchical models, which led to improved inventory management and reduced stockouts. This aligns well with your goal to advance retail merchandising and pricing analytics using AI. Our approach focuses on delivering scalable, AI-driven forecasting and optimization solutions that simplify complex data challenges, ensuring clear, actionable insights that drive smarter business decisions and operational efficiency. I’d love to chat about your project! The worst that can happen is you walk away with a free consultation. Regards, Nathan Holmes