Data Science & Engineering Solutions
We specialize in building predictive models, evaluating performance, and engineering robust data pipelines for collection, transformation, storage, and visualization.
Data Science
Model building and evaluation
Data Engineering
Collection, transformation, storage
Visualization
Interactive dashboards and reports
Our Data Science & Engineering Approach
Data Collection
- •Design and implement robust data collection pipelines
- •Collect from APIs, databases, files, and streaming sources
- •Ensure data quality and reliability
- •Handle multiple data formats and protocols
Data Transformation
- •Clean and validate raw data
- •Transform data into analysis-ready formats
- •Use modern ETL/ELT processes
- •Handle missing values and outliers
Data Storage
- •Architect scalable storage solutions
- •Implement data warehouses and data lakes
- •Leverage cloud platforms
- •Ensure data security and compliance
Model Development
- •Build predictive models
- •Use machine learning algorithms
- •Apply statistical methods
- •Leverage domain expertise
AI Model Architecture Design
- •Design and architect AI/ML model structures
- •Select appropriate neural network architectures
- •Feature engineering and selection
- •Model complexity optimization
Model Training & Hyperparameter Tuning
- •Train models with optimal hyperparameters
- •Automated hyperparameter optimization
- •Transfer learning and fine-tuning
- •Model performance optimization
Model Evaluation
- •Comprehensive evaluation
- •Cross-validation and testing
- •Performance metrics and bias detection
- •Model interpretability
Visualization & Deployment
- •Create interactive dashboards
- •Deploy models to production
- •Monitor model performance
- •Maintain and update models
Methodology & Delivery Approach
Our proven approach ensures successful data projects from concept to production
Agile / Iterative Delivery
We follow agile methodologies with iterative sprints, continuous feedback, and adaptive planning to deliver value incrementally and respond quickly to changing requirements.
MVP → Production Approach
Start with a Minimum Viable Product to validate concepts quickly, then iteratively enhance and scale to full production systems with robust architecture.
Data Governance & Compliance
Implement comprehensive data governance frameworks ensuring data quality, lineage tracking, and compliance with GDPR, CCPA, and industry-specific regulations.
Security-by-Design
Security is integrated from the ground up with encryption, access controls, audit logging, and regular security assessments to protect sensitive data.
Model Lifecycle Management
End-to-end model management including versioning, monitoring, retraining pipelines, and automated rollback capabilities to maintain model performance over time.
Our Team
Meet the experts behind AICE
Gregoire C
Early career at MIT then NASA on the latest AI models. Specialization in machine learning algorithms and model evaluation.
Florian W
Data engineer with experience in London and Swiss Romande, specializing in data pipelines, transformation, and cloud infrastructure.
Ready to Transform Your Data?
Partner with AICE to unlock the power of your data with expert data science and engineering solutions.
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Contact Information
Our team is ready to help you build robust data pipelines, develop predictive models, and create actionable insights from your data.
info@aice.com
Office
Avenue de Rumine 38
1005 Lausanne
Why Choose AICE
- • Expert data science and engineering
- • Production-ready solutions
- • End-to-end data services