Data Scientist (Data Visualisation) Offline

Description:

The position of Data Scientist (Data Visualisation) combines skills in the field of big data analysis and information visualization. The specialist in this role is responsible for transforming large and complex datasets into clear and informative visual representations. Below are the skills and responsibilities associated with this role:

Preferred Skills:

Data Analysis: A Data Scientist (Data Visualisation) specialist should possess deep data analysis skills, including the ability to identify patterns, trends, and key insights in large volumes of information.

Data Visualization: Proficiency in tools and techniques for data visualization. The ability to create graphics, charts, diagrams, graphs, and interactive dashboards to present data.

Design and Visual Style: Experience in design and an understanding of principles of visual communication. The ability to create visual components that are easy to read and convey information effectively.

Communication Skills: The ability to explain complex data and visualizations to colleagues and clients, as well as to listen to their feedback and improve visualizations as needed.

Responsibilities:

1. Data analysis: Collect, cleanse, and analyze large amounts of data to identify key findings and patterns. Prepare data for visualization.

2. Creating visualizations: Developing data visualizations to help users better understand information. This can include creating charts, graphs, diagrams, maps, and even three-dimensional data models. Testing of the graphs (visual elements) we have developed.

3. Interactive dashboards: Develop interactive dashboards that allow users to explore data independently and get the information they need. For example, using DataBox (or analogs), developing your own dashboards on Flask, FastAPI.

4. Performance optimization: Improving the performance of visualizations to work efficiently with large data sets.

5. Collaboration: Working closely with data analysts, data engineers, and customers to meet their data visualization needs.

6. Training and feedback: Training colleagues and users on how to work with data visualizations and taking their feedback into account to continuously improve visual solutions.

7. Keeping up with trends: Keeping up to date with the latest trends in data visualization and implementing them in your work.

Requirements:

1. Minimum of 2 years as a Python Developer or Data Scientist;
2. Knowledge of pandas, libraries for visualizing, experience with API, DataBox, Google Sheets, and Google Scripts (will be a plus);
3. Experience in the area of visualizations and Big Data;
4. Ability to understand business requirements and translate them into technical requirements starting from architecture level and technological stack proposal;
5. Ability to go deep into technical details keeping in mind the whole project scope and architecture;
6. Experience in collaboration with cross-functional teams to design, develop, and implement new features;
7. Very good written and verbal communication skills in English;
8. Familiarity with Azure;

Would be a plus

● Understanding of the analytics and statistics;

● A knack for benchmarking page performance and implementing optimization;

● Experience in pixel-perfect and trendy visuals;