I can help you conduct time series forecasting using Python

  • 4.1
  • (5)
I can help you conduct time series forecasting using Python
I can help you conduct time series forecasting using Python
I can help you conduct time series forecasting using Python
I can help you conduct time series forecasting using Python
I can help you conduct time series forecasting using Python
I can help you conduct time series forecasting using Python

Project Details

Why Hire Me?

I have 7+ years of hands-on experience in time series forecasting using Python, having developed predictive models for industries including retail, finance, climate, and operations. My solutions are business-focused and technically sound.

Why Clients Choose Me:

  • Deep expertise in ARIMA, SARIMA, Holt-Winters, Prophet, and LSTM

  • Proficient in pandas, statsmodels, scikit-learn, fbprophet, matplotlib

  • Able to handle messy, irregular, or seasonal data

  • Strong at communicating forecasts through visualizations and executive summaries

  • Deliver clear, structured reports with Python + Jupyter Notebooks + R Markdown (via reticulate)

  • Trusted by clients for reliable delivery and industry-specific modeling


What I Need to Start Your Work

Please provide the following before we begin the forecasting process:

1) Project Scope and Objectives

  • Purpose of the forecasting project

  • Business decisions you intend to support

  • Research questions or hypotheses

2) Time Series Data Details

  • File format (CSV, Excel, database)

  • Frequency (daily, weekly, monthly, etc.)

  • Duration covered by the data

  • Target variable(s) and known seasonality/cycles

  • Whether the data has been cleaned/preprocessed

3) Preferred Tools and Techniques

  • Forecasting models to use (ARIMA, Prophet, ML models like LSTM or Random Forest)

  • Libraries preferred: statsmodels, fbprophet, sklearn, pmdarima, etc.

  • Any existing Python code, scripts, or notebooks

4) Report Structure and Deliverables

  • Required sections (e.g., Executive Summary, Model Development, Forecast Plots, Residual Diagnostics)

  • Format preference: PDF, Word, or Notebook

  • Level of technicality: beginner-friendly or for expert audiences

  • Type and number of visualizations

5) Privacy and Confidentiality Requirements

  • NDA or confidentiality constraints

  • GDPR/CCPA or other compliance needs

  • Secure method of data transfer

6) Project Timeline

  • Final deadline

  • Intermediate check-ins or milestones

7) Communication Preferences

  • Preferred platform (e.g., WhatsApp, Google Meet, Email)

  • Update frequency

8) Any Additional Instructions

  • Specific formatting, citations, client-specific language

  • Domain-specific concerns (e.g., stock price volatility, retail seasonality)

  • Examples to follow (if available)

Portfolio

Sales Forecasting for a U.S. Retail Chain Using ARIMA and Prophet in Python

Built monthly sales forecasts for a multi-location U.S. retail chain using Python. Delivered a comparison of ARIMA and Prophet models with actionable insights for inventory and staffing decisions.

Python-Based Forecasting of Daily Ride Demand for an Urban U.S. Transportation Startup

Used SARIMA and Prophet models in Python to forecast daily ride demand for a micromobility startup. The forecasts enabled real-time fleet allocation, cost control, and surge pricing decisions across urban zones.

U.S. Inflation Forecasting with Python Time Series Models: A Monthly Economic Outlook Tool

Developed a Python-based forecasting model using CPI, unemployment, and commodity trends to project U.S. inflation over 12 months. The tool enabled clients to simulate inflation risk and incorporate projections into financial planning and procurement decisions.

Process

Customer Reviews

5 reviews for this Gig ★★★★☆ 4.1

5 Stars
(1)
4 Stars
(4)
3 Stars
(0)
2 Stars
(0)
1 Stars
(0)
Rating Breakdown
  • Seller communication level ★ 4
  • Recommend to a friend ★ 4
  • Service as described ★ 4.2

🇪🇬
Sara El-Gamal
4 5 July 2025

my dataset was huge with missing values he handled it so well and the dashboard he gave was very easy to show my client



🇺🇸
Felix Johnson
4 5 July 2025

he did the forecast right but took one extra day than promised but result was worth it so not complaining much



🇬🇧
Sameer Bhatt
3.7 5 July 2025

super fast delivery and he explained all steps clearly i used it for my final year thesis got an A



🇩🇪
Clara Müller
4 5 July 2025

good use of ARIMA and plots were neat but i had to ask for clarification on seasonality part



🇯🇵
Hiroshi Tanaka
4.7 5 July 2025

he used Prophet and cleaned up my messy retail data got the forecast ready within 2 days very reliable work


Doesn’t matter you are a company or a student!

Frequently Asked Questions

I will give you the price after checking the project details.

It will be given after discussion by looking at the complexity of the task and our mutual understanding.

You can trust me because I have been working as a data analyst from past 7 years and have worked on projects across multiple industries.

Refund will be discussed after our mutual discussion and complexity of task. If I completely fail to deliver the task, I will refund 100% of the amount.

50% will be in advance and 50% after the delivery of complete task. This is negotiable and can be discussed and finalized after our discussion.

Data confidentiality is paramount. I adhere to strict data security protocols and ensure that all client information is handled with the utmost discretion and security.

Yes, I have experience across various industries and can tailor my approach to meet the specific needs and nuances of your sector.

I can analyze and forecast a wide range of time series data, including financial, economic, sales, and environmental data, using Python’s extensive data analysis capabilities.

Absolutely, I specialize in tailoring forecasting models in Python to specific industries or business needs, ensuring the forecasts are relevant and insightful.

Yes, I offer comprehensive guidance on interpreting forecast results, providing actionable insights that can be directly applied to strategic decision-making.

I ensure accuracy and reliability by using proven forecasting models, performing rigorous model validation, and staying abreast of the latest developments in time series analysis.