You will get a New or Improved Machine Learning Model for Your Data
Project details
You will get a machine learning solution tailored to your data and business objectives. Whether you need a new model built from scratch, improvements to an existing model, or help understanding why current approaches are underperforming, I can help.
I hold a dual PhD in Mechanical Engineering and Computational Mathematics and have extensive experience developing machine learning algorithms for complex, noisy, and real-world datasets. My work has included time-series forecasting, signal processing, classification, optimization, and predictive modeling across engineering, scientific, and biological applications.
Unlike many freelancers who focus solely on model training, I emphasize understanding the data, identifying bottlenecks, validating results, and providing clear recommendations. Every project includes rigorous evaluation and transparent communication so you understand both what the model can do and its limitations.
Whether you're a startup, researcher, engineer, or business owner, you'll receive a professional solution backed by strong analytical and machine learning expertise.
I hold a dual PhD in Mechanical Engineering and Computational Mathematics and have extensive experience developing machine learning algorithms for complex, noisy, and real-world datasets. My work has included time-series forecasting, signal processing, classification, optimization, and predictive modeling across engineering, scientific, and biological applications.
Unlike many freelancers who focus solely on model training, I emphasize understanding the data, identifying bottlenecks, validating results, and providing clear recommendations. Every project includes rigorous evaluation and transparent communication so you understand both what the model can do and its limitations.
Whether you're a startup, researcher, engineer, or business owner, you'll receive a professional solution backed by strong analytical and machine learning expertise.
What's included
| Service Tiers |
Starter
$150
|
Standard
$500
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 7 days | 4 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 3 | 8 | 15 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$50
Additional Model Variation
(+ 2 Days)
+$100
Model Documentation
(+ 3 Days)
+$200
Source Code
(+ 2 Days)
+$100Frequently asked questions
About Sunia
PhD Data Scientist | Forecasting, Machine Learning & Statistics
Haslett, United States - 8:40 pm local time
I currently work as a Research Scientist at the University of Michigan and hold a dual PhD in Mechanical Engineering and Computational Mathematics. My expertise includes time-series forecasting, statistical modeling, machine learning, predictive analytics, signal processing, uncertainty quantification, and decision-support systems.
I specialize in challenging datasets where noise, missing information, uncertainty, or complex system behavior make standard approaches unreliable.
What I can help you with:
• Time-series forecasting and predictive analytics
• Machine learning model development and evaluation
• Statistical analysis and uncertainty quantification
• Predictive modeling for business, research, and engineering decisions
• Classification on difficult or noisy datasets
• Feature engineering, data preprocessing, and model validation
• Model debugging and performance improvement
• End-to-end ML pipelines in Python
• Signal processing and biomedical data analysis
• Simulation, surrogate modeling, and optimization workflows
• Decision-support models for real-world systems
Experience Highlights:
• Developed machine-learning models for biomedical signal classification that improved accuracy by 15% over conventional feature-engineering approaches.
• Developed custom statistical and machine-learning algorithms for identifying patterns, data drift, and behavioral changes in noisy, uncertain, and stochastic datasets.
• Built predictive models and surrogate modeling systems that replaced computationally expensive simulations, enabling rapid design evaluation and optimization.
• Conducted research in forecasting, stochastic systems, machine learning, and scientific computing, resulting in peer-reviewed publications, open-source software contributions, and conference presentations.
Tools & Technologies:
Python, Pandas, NumPy, SciPy, scikit-learn, XGBoost, TensorFlow, PyTorch, SQL, Jupyter, Matplotlib, Statistical Modeling, Machine Learning, Time-Series Forecasting, Predictive Modeling, Signal Processing, Data Analysis, Feature Engineering, Model Validation, Optimization, Scientific Computing.
My Approach:
Most machine-learning problems do not fail because of the model itself - they fail because the data is noisy, incomplete, poorly structured, or difficult to interpret. My focus is on building reliable models, validating assumptions, reducing overfitting, and delivering results that are useful for real-world decisions.
If you're working on forecasting, predictive modeling, machine learning, statistical analysis, model validation, or complex data challenges, I’d be happy to discuss how I can help.
Steps for completing your project
After purchasing the project, send requirements so Sunia can start the project.
Delivery time starts when Sunia receives requirements from you.
Sunia works on your project following the steps below.
Revisions may occur after the delivery date.
Project Discovery & Data Review
Review project goals, available data, existing models, and technical requirements.
Data Assessment & Preprocessing
Evaluate data quality, identify potential issues, clean and prepare data for modeling.