services
Rooftop's Data Science Competencies
When creating data intelligence solutions, we use our business economic knowledge and various data science skills and apply open source applications and cloud IT platforms.
Rooftop Analytics’ starting point is always founded in the client's unique problem and our approach always follows Rooftop’s Predictive Analytics Model. Our choice of applications for developing algorithms and the use of IT platform, is carefully aligned with the customer’s preferences.
In our Business Data Science Center of Excellence, we are always fully updated on the new application packages (and libraries) that continuously are becoming available. We excel in developing our data science skillsets by getting hands-on experience with the newest data science techniques. We do this in the context of real business problems, as we leverage statistical and economical domain knowledge obtaining state-of-the-art data intelligence solutions.
Rooftop's Data Science Skills
Within the umbrella of data science, Rooftop Analytics offers the following data science skills.
ML og AI competences
- Machine learning; Supervised learning, Unsupervised learning, Reinforcement learning
- Computer vision with extended skills in OpenCV and Scikit-image
- Natural Language processing (NLP) with extended skills in BERT, GPT-3, and Scapy
- Python with extended skills in Tensorflow and Pytorch
Visualizations
- Python and R visualization packages with extended skills in ggplot and plotly
- Tableau
- Microsoft Power BI
Cloud services applications from
- Microsoft Azure
- Amazon Web Services
- Google Cloud Platform
Rooftop's Domain Competencies
We believe that it requires strong domain knowledge in business economics and statistics competentices to apply the most appropriate data science techniques when creating the best data intelligence solutions. The business problem and the context in which it resides, must be well understood and carefully disentangled before the appropriate machine learning algorithms can be developed.
Economics and statistical domain knowledge being applied
- Time series analysis (short and long run)
- Causal identification and estimation
- Market price formation in commodity, forex, financial, and retail markets
- Price elasticity and substitution effects
- Risk and uncertainty assessment and estimation
- Supply and demand optimization
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Our model secures we uncover the topic, are firm in our approach to develop the algorithm, and work agile.
We are a team with unique competences in business data science and capable of seeing extraordinary opportunities in data.