A data science service for smart business insight
Data science is becoming more and more important in different domains such as e-commerce, healthcare, smart energy, business, social media, insurance, and research & development, to name a few.
Data science projects require multiple competences such as programming, statistical and analytical skills as well as high quality communication and visualization. As a self-employed data scientist, I offer profound expertise with different data projects.
Data science projects require multiple competences such as programming, statistical and analytical skills as well as high quality communication and visualization. As a self-employed data scientist, I offer profound expertise with different data projects.
A few examples of services provided:
- Feasibility and quality analyses
- Formulation of data science question(s)
- Data / feature preprocessing, such as cleaning, merging, data transformations, treatment of outliers and missing values
- Visualizations and descriptive statistics to get smart business insight
- Machine learning, statistical modeling, multivariate statistics
- Deployment of Dashboards at cloud computing services such as AWS
- Data report, giving clear insight into your key questions
- Communication and regular skype or face-to-face meetings (in Geneva Area, Switzerland / France)
Please visit the e-commerce case analyses for a concrete example.
Below a simplified illustration of a dashboard, that can be visited online:
Key service values
- Goal oriented (business value)
- National and international service
- Rapid hands-on implementation
- Regular personal (skype) contact
- Clear data communication and visualization during the whole data science process.
Data science toolbox
Python - numpy, pandas, scikit learn, keras, matplotlib, seaborn, plotly
R - data.table, dplyr, baseplot, ggplot
Cloud computing - amazon web services (AWS)
Visualization - plotly, matplotlib, seaborn (Python), tableau
Communication - jupyter notebook, R studio
Deployment - Dash (Python), Shiny (R)
Big data - H2O.ai, spark
OS / Software - linux, docker
Various - google analytics, matlab / octave GNU
This is just a short list, of course there are many excellent tools available.
You are invited to contact me for questions: rrighart at googlemail dot com
R - data.table, dplyr, baseplot, ggplot
Cloud computing - amazon web services (AWS)
Visualization - plotly, matplotlib, seaborn (Python), tableau
Communication - jupyter notebook, R studio
Deployment - Dash (Python), Shiny (R)
Big data - H2O.ai, spark
OS / Software - linux, docker
Various - google analytics, matlab / octave GNU
This is just a short list, of course there are many excellent tools available.
You are invited to contact me for questions: rrighart at googlemail dot com
Email: rrighart@googlemail.com
