Machine Learning Engineer Needed for Sales Data Analysis – Summer Plan

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@nrajuu07

I'm a data analyst experienced in sales forecasting and retail analytics. I'll clean and analyze your 12-month sales history in Python, surface key trends and purchasing patterns, and deliver a concise manager-friendly report covering recommended product collections, discount structures, social media marketing ideas, and a numerical summer sales forecast — all figures fully traceable to the notebook with MAE/MAPE shown. Actionable insights ready to use the day after delivery. Share the file and I'll get started immediately.

@KolmanOuassou

Hi, I am a data analyst/statistician and Economist with more than 6 years of experience. I can do your project, Please take time to check my profile and then you decide to contact me.

@SakibKaiser

Hello, As a Data Analyst and AI Engineer who has successfully completed 30+ predictive analytics projects, I specialize in bridging the gap between Python data modeling and practical business decisions. I will deliver the complete package within 1 day: • Executive Report (PDF/Deck): A highly practical, concise summary detailing key yearly trends, recommended summer product collections, data-backed discount structures, and targeted social media marketing ideas. • Numerical Forecast: A clear summer sales projection, explicitly detailing the underlying assumptions and forecast error metrics (MAE/MAPE) so you know exactly how reliable the model is. • Traceable Python Pipeline: You will receive the fully commented Jupyter Notebook (using Pandas/Scikit-learn) with clean Matplotlib/Seaborn visuals, ensuring every single figure in the report is 100% traceable to the code. I am ready to turn your raw data into an action plan you can execute on day one. Please share the Excel/CSV file, and I will get started immediately. Best regards, Shakib A.

@maxscender

I can help you transform your sales history into a data-driven summer strategy. I will use Python to perform time-series decomposition to isolate seasonal trends and apply association rule learning to identify high-conversion product bundles. My forecasting approach will include transparent MAE/MAPE metrics to ensure the summer projections are grounded in statistical reality. You will receive a clean code notebook for verification and a concise report that translates data patterns into specific discount thresholds and marketing hooks ready for immediate execution.

@mzdesmag

Hello sir, Did go through your job description and glad to share that I have enormous experience in working with Machine Learning Engineer Needed for Sales Data Analysis – Summer Plan I'm a seasoned programmer and Engineer with quality experience in Flutter, React, Node.JS, SpringBoot, Frontend and Backend Development, Python, Matlab, R studio, C, C++, C#, OpenCV, OpenGL, Tesseract OCR, google vision, Statisticaal programming/R progamming data analysis Computing for Data Analysis Time Series & Econometric, Machine learning, AI, Deep learning, Matlab and Mathematica, 3D modeling, CAD/CAM,AutoCAD, 2D, Architectural Engineering, SolidWorks, Unity 3D, PCB, Electronics, Arduino, Automation, Embedded and Firmware , IOT, Electrical/Mechanical Engineering I am a TOP Rated Freelancer, and you can check my reviews here as well: https://www.freelancer.com/u/mzdesmag. Looking forward to potentially working together on this project. Thanks and Best regards, Adekunle.

@Microlent

Turning your twelve months of sales history into an actionable summer roadmap requires looking past the raw numbers to find the behavioral triggers that drive your peaks. It sounds like the real goal here is a strategy that links your inventory levels directly to social media tactics. I've handled similar data modeling for retail projects where I used Python and pandas to turn messy CSV files into clear purchasing patterns. I find that forecasting works best when we explicitly document the underlying assumptions, especially for seasonal shifts like summer. I'll make sure the MAE and MAPE metrics are transparent so you know exactly how much weight to put on the forecast figures. I generally start by cleaning the raw file and building a visualization of the last twelve months. This usually reveals the exact week your summer surges begin, which dictates when you should launch those social media offers. I can put together a brief, manager-friendly summary report for free so you can see my approach first. ~ Rajesh

@vanhuy19892011

Hi, I can help analyze your last twelve months of sales data and turn it into a clear, practical summer action plan. My workflow would be to clean and explore the Excel/CSV file in Python using pandas, identify sales trends, product patterns, seasonality, and customer purchasing behavior, then build a simple forecast with clear error metrics such as MAE or MAPE. I can also include charts to make the findings easy to understand, but the final report will stay manager-friendly and focused on decisions you can act on. The deliverables would include the cleaned notebook/code, traceable calculations, visual trend summaries, product collection recommendations, offer and discount suggestions, social media marketing ideas backed by the data, and a numerical summer sales forecast with assumptions clearly explained. I’ll make sure every recommendation is tied directly to the discovered patterns rather than giving generic marketing advice. P.S. My goal is to give you a report that is not just analytical, but useful the next day for planning product focus, discounts, and summer marketing.

@HNamdar

I can see you need someone to dig into your last twelve months of Excel/CSV sales data to surface meaningful trends and then translate those findings into a concrete summer-season action plan. This is exactly the kind of end-to-end analysis work I do, going beyond surface-level charts to identify what is actually driving performance shifts. With my PhD research background and expertise in Python for data analysis, I can handle the full workflow: data cleaning, trend identification, seasonality analysis, and a clear written action plan with specific recommendations. I work comfortably in pandas, matplotlib, and seaborn for visualization. What format would you like the final deliverable in, and are there specific product categories or regions you want me to focus on?

@southa5

As a seasoned and dedicated machine learning engineer with a strong research background in computational science, I am confident in my ability to parse through your sales data and extract the most valuable insights. My proficiency in Python, pandas, scikit-learn, and TensorFlow aligns perfectly with the tools you specifically requested. This means I can not just clean and model your data but also create highly tailored visualizations using Seaborn or Matplotlib that will transform complexity into comprehensibility for your managers.

@umairinayat1

As an AI/ML Engineer with a specialization in computer vision, my expertise in data preprocessing, model training, and real-time deployment aligns perfectly with your project on sales data analysis. My vast experience applies various techniques from YOLO to MediaPipe, ensuring that the results are comprehensive and insightful. Notably, my work in object detection on live CCTV feeds and facial analysis for an AR face filter system exemplifies my ability to gain indispensable insights from visual analytics. Implicating applied knowledge from Object-oriented programming and deep learning techniques like YOLOv8, Faster R-CNN and HRNet, I was able to build systems that outperformed the state of art (SOTA) by a significant margin (3% for satellite object detection model). I am no stranger to dealing with enormous data sets, cleansing it, exploring it, processing it before giving it a meaningful shape. Extending beyond just technical skills,I also prioritize the functionalities of business operations. Rest assured, my managerial report will offer clear trends and actionable recommendations that reflect the specific products, discounts structures and marketing approaches you need for the upcoming summer season. My focus lies in delivering high-quality work equipped with thorough documentation which can be easily validated through metrics like MAE or MAPE.

@thithu36722

Being a Full-Stack Developer and Certified SEO Strategist with a background in Business Administration, I perfectly align with your project's needs. My expertise in Python-based Data Analysis, which includes libraries such as pandas and scikit-learn, will allow me to clean, explore, and model the raw sales data seamlessly. Additionally, my knack for visualizing complex data through matplotlib or seaborn charts ensures the delivery of manager-friendly yet insightful reports. Having successfully transformed data into actionable insights for various businesses over the years, I am confident in my ability to identify key sales trends and purchasing patterns from your last twelve months' sales records. Moreover, leveraging my AI and GEO expertise will provide you an accurate numerical forecast of expected summer sales empowering you with informed decisions. Moreover, I assure you that all presented figures will be linked back to the code or notebook provided to ensure full transparency and accountability. Lastly, my proven ability to bridge technical development with profitable marketing strategies guarantees recommendations that are not just specific and actionable but also tied directly to the identified patterns. Your satisfaction matters to me;

@ahtishamulhaque1

With over a decade of expertise in full-stack software engineering and an extensive repertoire for delivering business-driven results, I am the ideal candidate to spearhead your data analysis project. Not only do I have vast experience with ML and Python, similar to the tools and libraries you mentioned, but my approach to any project is strategic, detail-oriented and focused on producing actionable insights. Through this engagement, I will offer not just an insightful report on the last twelve months of your sales data - but a coherent action plan tailored specifically for the upcoming summer-season. My strength lies in combining technical skills with business acumen. Every nugget of information mined from your data will be meticulously organized, analyzed, and presented through interactive charts using tools like matplotlib and seaborn. Finally, one of my core principles is to deliver not just completed work, but tangible value for your business. For this reason, in addition to the descriptive sales trends you desire, my report will also encompass clear recommendations on product collections resonant for summer beating out competition. My ideas will be backed by empirical evidence from the dataset provided. With forecast error metrics included, you'll have solid estimates of expected summer sales that will help shape your budgeting decisions. Looking forward to taking your data analysis beyond numbers to deliver insights ready to set you apart in the approaching season.

@nintysix96

The bid amount and timeline above are rough placeholders , we'll sharpen both once we've had a quick look at your file and talked through what you need. From what you've described, you have a full year of sales history in Excel/CSV and you need someone to dig into it properly: find the real patterns, not just surface-level numbers, and turn those findings into a practical summer plan your team can actually act on. The deliverable needs to hold up to scrutiny too , every figure traceable to the notebook, forecast error metrics shown, recommendations tied directly to what the data says. That's a tighter brief than most clients ask for, and we like that. Here's how we'd approach this: - Data cleaning and exploration: load the CSV with pandas, handle missing values, normalize date fields, and run an initial EDA to spot outliers and seasonal shape before touching any models. - Trend and pattern analysis: decompose the time series (STL or classical decomposition), identify top-performing SKUs, purchasing cadence, and category-level swings across the twelve-month window. - Forecasting: fit a regression or lightweight ensemble (scikit-learn, possibly Prophet for the seasonal component) with MAE and MAPE reported clearly so you can judge confidence before acting on any number. - Recommendations layer: map forecast output to specific product collections, discount thresholds, and social timing windows , each one cited back to a chart or table in the notebook. - Report: a clean PDF or slide deck written for a manager, not a data scientist , plain language, visuals from matplotlib/seaborn, and an action checklist at the end. After a short scope chat we'll put together a written proposal covering deliverables, timeline, and a firm price. Want to jump on a quick call this week to walk through the data structure and any business context we should keep in mind? Best, 96 Studio

@SantiagoJoaquin7

Hello, I have reviewed your project and can help transform your sales data into actionable insights and a practical strategy for the upcoming summer season. I can take care of cleaning, exploring, and analyzing the Excel/CSV data using Python (Pandas, NumPy, Scikit-learn, and visualization libraries), identifying sales trends, purchasing patterns, top-performing products, seasonal behaviors, and opportunities for growth. In addition, I will develop a sales forecast supported by appropriate validation metrics such as MAE and MAPE, ensuring that all conclusions and recommendations are fully traceable to the underlying analysis and code. The final deliverables will include a concise executive report with visualizations, key findings, product recommendations, discount strategies, marketing insights, and a clear forecast for the summer period, focusing on practical actions that can support business decisions immediately. I have experience working with data analysis, reporting, Business Intelligence, and data-driven decision-making. Before moving forward, I would like to clarify a few points: • Approximately how many records are included in the dataset? • How many years of sales history are available? • Is the forecast expected at the overall sales level or by product/category? I look forward to discussing the project further.

@agustingonzalog

Hello, I can help you analyze your sales data and build a summer action plan. Approach: • Clean, explore, and model your CSV data in Python (pandas, scikit-learn) • Visual explanations with matplotlib/seaborn charts • All figures traceable back to the notebook Deliverables: • Short report (PDF) covering key trends, recommended product collections, offer structures, social-media ideas, and a numerical forecast with error metrics (MAE/MAPE) Technologies: • Python, pandas, scikit-learn, matplotlib, seaborn, Excel, statistics Timeline: • 3–4 days Goal: To deliver actionable, manager-friendly insights you can use the next day. Ready to get started. Agustin