You will get Marketing Attribution ML Model
Project details
My approach stands out by combining advanced machine learning with real-time data analysis, ensuring unparalleled accuracy in attribution. Unlike traditional models, mine continually adapts to market dynamics, providing precise, actionable insights and optimized budget allocation for maximum ROI.
Machine Learning Tools
Kubeflow, NumPy, pandas, PyMC, R, scikit-learn, SciPy, SQL, XGBoostWhat's included
| Service Tiers |
Starter
$1,000
|
Standard
$2,500
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 30 days |
Number of Revisions | 0 | 1 | 3 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | - |
Source Code |
About Michael
Data Scientist | python | AI Specialist
Orange, United States - 5:50 am local time
I'm Michael Sims but most people just call me Sims. I'm an experienced Data Scientist specializing in marketing analytics, e-commerce optimization, and artificial intelligence. With a Bachelor's degree in Advanced Mathematics from SFSU and a Master's degree in Applied Statistics from CSULB, I bring expertise in predictive analytics, statistical modeling, AI, and data-driven decision-making.
My hands-on experience at top marketing agencies and e-commerce firms includes optimizing advertising spend, predicting lead conversions, and enhancing marketing ROI for brands like Native Skin Care and Pit Viper.
Currently, I'm working at leading project management software company where I built an automated salesbot to assist the sales team in outreach, and also prepping prospective buyers to be sales ready, as well as identifying and closing self serve customers. Looking to expand my network and help big and small companies alike grow their business. Let's collaborate to drive business success through data-driven strategies. Reach out to explore potential opportunities.
Best regards,
Sims
Steps for completing your project
After purchasing the project, send requirements so Michael can start the project.
Delivery time starts when Michael receives requirements from you.
Michael works on your project following the steps below.
Revisions may occur after the delivery date.
Data Collection and Preparation
Gather and preprocess the data collected by pixels, which includes user interactions, timestamps, and associated metadata.
Feature Engineering
Create meaningful features from the raw data. This may include user session data, time spent on pages, sequence of interactions, and other contextual information.