You will get Proven ML Services: Scoping, POC, Production-Ready System
Project details
Fortune 500 ML Engineering with 3-Tier Fixed-Price Structure
I build ML systems that last years, not notebooks that get thrown away. My production systems have captured tens of millions in business value and still run years later.
Why the 3-Tier Approach?
Most ML projects fail due to poor scoping. This structure protects your investment through progressive validation:
TIER 1: Project Scoping & Feasibility ($750, 7 days)
Validate ML is the right solution before larger investment. Includes data assessment, feasibility analysis, and custom proposal. Honest expert guidance - even if the answer is "ML won't work."
TIER 2: Proof of Concept ($4,000, 14 days)
Prove ML works with 3-5 tested models in Jupyter notebook. Comprehensive EDA, performance analysis, and Go/No-Go recommendation. If it doesn't work, you saved $12k.
TIER 3: Production-Ready Package ($12,000, 28 days)
Production system with Python package, FastAPI service, Docker container, explainability, tests, and documentation. I deliver tested system; your team deploys.
My Promise: Fortune 500 rigor, honest assessments, clear boundaries. No surprises, no scope creep.
Start with Tier 1 or message me to discuss your project.
I build ML systems that last years, not notebooks that get thrown away. My production systems have captured tens of millions in business value and still run years later.
Why the 3-Tier Approach?
Most ML projects fail due to poor scoping. This structure protects your investment through progressive validation:
TIER 1: Project Scoping & Feasibility ($750, 7 days)
Validate ML is the right solution before larger investment. Includes data assessment, feasibility analysis, and custom proposal. Honest expert guidance - even if the answer is "ML won't work."
TIER 2: Proof of Concept ($4,000, 14 days)
Prove ML works with 3-5 tested models in Jupyter notebook. Comprehensive EDA, performance analysis, and Go/No-Go recommendation. If it doesn't work, you saved $12k.
TIER 3: Production-Ready Package ($12,000, 28 days)
Production system with Python package, FastAPI service, Docker container, explainability, tests, and documentation. I deliver tested system; your team deploys.
My Promise: Fortune 500 rigor, honest assessments, clear boundaries. No surprises, no scope creep.
Start with Tier 1 or message me to discuss your project.
Machine Learning Tools
MLflow, NumPy, PyMC, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$750
|
Standard
$4,000
|
Advanced
$12,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 28 days |
Number of Revisions | 1 | 1 | 1 |
Number of Model Variations | 0 | 3 | 3 |
Number of Scenarios | 1 | 1 | 1 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$350 - $3,600Frequently asked questions
About Tomislav
Decision Scientist | Data Scientist | Analytics Consultant
Amsterdam, Netherlands - 6:57 pm local time
CORE EXPERTISE
Machine Learning & AI: Python, PyTorch, Scikit-learn, XGBoost, Time Series Forecasting (Prophet, DARTS, Nixtla stack), Causal Inference, A/B Testing, Bayesian Modeling (PyMC)
LLM & RAG: OpenAI, HuggingFace, LangChain, LangGraph, ChromaDB, FAISS
MLOps & Cloud: Docker, Kubernetes, MLFlow, GitHub Actions, Databricks, AWS (S3, SageMaker, Redshift), Azure (ML, Synapse, ADF), databricks, model monitoring, drift detection
Data Engineering: PySpark, Pandas, Polars, ETL pipelines, data quality frameworks (Great Expectations)
SPECIALIZED SOLUTIONS
✓ Media Mix Modeling (MMM): Led Heineken's most successful analytics project—captured tens of millions in value first year. Bayesian attribution modeling, channel optimization, ROI measurement, budget allocation.
✓ IoT ML Solutions: Equipment monitoring, predictive maintenance, sensor data analytics, anomaly detection at scale—deployed solutions still running 3+ years later.
✓ RAG & LLM Applications: Production knowledge retrieval systems for financial services. Semantic search, document analysis, evaluation frameworks, prompt optimization.
✓ Entity Deduplication & Record Linkage: Fuzzy matching, probabilistic record matching at scale (millions of records), customer/product master data.
✓ Supply Chain & Logistics: Demand forecasting, inventory optimization, route planning, cost-benefit simulation.
WHY WORK WITH ME?
→ End-to-End Delivery: From data architecture to production deployment - I handle the full ML lifecycle so you don't need multiple specialists.
→ Business Impact: My solutions deliver measurable ROI and remain operational years after launch. One client brought me back to improve my original work - the ultimate validation.
→ Startup-Ready: Modern tech stack (FastAPI, Streamlit, containerized deployments), rapid prototyping, pragmatic solutions over academic theory.
→ Scientific Rigor: PhD in Physical Chemistry from University of Amsterdam - I bring systematic methodology to ambiguous business problems.
Looking for ML/AI expertise that delivers real business value? Let's discuss how my specialized skills can accelerate your data science initiatives.
Steps for completing your project
After purchasing the project, send requirements so Tomislav can start the project.
Delivery time starts when Tomislav receives requirements from you.
Tomislav works on your project following the steps below.
Revisions may occur after the delivery date.
Initial Consultation & Scope Alignment [All Tiers]
Kickoff call to understand your problem, data situation, and success criteria. For Tier 1: Define assessment scope. For Tier 2: Confirm POC approach. For Tier 3: Review validated model and production requirements.
Data Assessment & Feasibility Analysis [Tier 1 Only]
Main Tier 1 deliverable: Review data quality, assess ML viability, and provide honest feasibility analysis. Delivers custom proposal with fixed-price quote for Tier 2 implementation if project is feasible.