You will get Machine Learning Model Development and Deployment
Rising Talent
Rising Talent
Project details
You'll get a production-quality machine learning model tailored to your data and business objectives, complete with clean source code, evaluation metrics, and clear documentation. With over six years of experience in data science and machine learning across industries—including energy, government, and consumer products—I specialize in building end-to-end solutions from raw data to deployment-ready pipelines. My work spans statistical modeling, deep learning, NLP, geospatial analytics, and Bayesian methods using tools like Python, R, scikit-learn, PyTorch, TensorFlow, and PyMC. Every deliverable is rigorously validated and clearly documented so you can confidently put it into production.
Machine Learning Tools
H2O, Keras, MLflow, NLTK, NumPy, OpenCV, pandas, PyMC, Python, PyTorch, R, scikit-learn, SciPy, SQL, TensorFlow, Theano, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,500
|
Advanced
$3,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 30 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 2 | 5 |
Number of Graphs/Charts | 2 | 5 | 10 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$75
Additional Model Variation
(+ 7 Days)
+$400
Additional Scenario
(+ 7 Days)
+$300
Additional Graph/Chart
(+ 1 Day)
+$50
Model Validation/Testing
(+ 7 Days)
+$250
Model Documentation
(+ 7 Days)
+$200
Data Source Connectivity
(+ 7 Days)
+$300Frequently asked questions
About Benton
Data Scientist
Clayton, United States - 6:28 am local time
Here’s an outline of my core skills and areas of expertise:
Machine Learning & AI:
- Developing and deploying end-to-end ML solutions and MLOps pipelines.
- Advanced statistical modeling, classification, time-series forecasting, and recommendation engines.
- Deep Learning (PyTorch, TensorFlow, Keras) for complex pattern recognition.
- Natural Language Processing (NLP), including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems (e.g., LangChain).
Geospatial Analysis & Development:
- Geospatial AI model design and implementation (e.g., for urban growth monitoring, species distribution).
- Processing and analyzing satellite imagery (e.g., Sentinel-2) and integrating with foundation models (e.g., Clay Foundation Model).
- Proficiency with GIS software (Esri ArcGIS, QGIS, GRASS GIS) and geospatial libraries.
- Spatial statistics and developing reproducible geospatial workflows.
Data Engineering & Cloud Technologies:
- Designing and implementing CI/CD data pipelines and ETL processes.
- Cloud Platforms: AWS (SaaS, SageMaker), Azure (DevOps), Databricks.
- Database Management: SQL/NoSQL, PostgreSQL.
- MLOps Platforms: Dataiku, DataRobot, MLflow, Domino Data Lab.
Programming & Software Development:
- Languages: Python, R, SAS, SQL, JavaScript/HTML/CSS.
- Version Control: Git (Azure DevOps, GitHub).
- Dashboarding & Visualization: R Shiny, Power BI, Dash.
Professional & Communication:
- Translating complex business requirements into scalable technical solutions.
- Effective communication with technical and non-technical stakeholders.
- Proven ability to work independently and collaboratively in dynamic team environments.
- Strong problem-solving skills with a commitment to continuous learning and delivering high-impact results.
Steps for completing your project
After purchasing the project, send requirements so Benton can start the project.
Delivery time starts when Benton receives requirements from you.
Benton works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Scoping
Review your dataset and requirements, clarify objectives, and define success criteria.
Data Preprocessing
Clean, transform, and engineer features from the raw data.