Possible Activities Of A Data Scientist
The data miner can monitor and animate research and development partnerships for new data mining tools with schools and universities.
Development Of Support Tools For Internal Customers
- Participate in the implementation of the company’s marketing strategy.
- Analyze all commercial data to develop effective decision support systems.
- Participate in the development of the company’s commercial performance indicators.
- Provide product managers with statistical decision-making levers for the conduct and analysis of prospecting campaigns.
- Carry out statistical studies for internal clients or general management.
- Lead workshops to express internal needs and write specifications.
- Write and write the specification of needs for CIOs or project management.
- Determine the dynamic and multidimensional reporting tools (OLAP).
- Present the results of studies carried out to internal clients.
- Train users in IT and decision-making tools.
- Animate meetings, organize and plan the interventions of a team.
- Ensure the recruitment and skills development of employees.
- Manage a budget and evaluate the cost of interventions.
- Size the projects and define the technical and methodological choices of interventions.
Context And Factors Of Evolution Of The Profession
In recent years, the volume and specification of consumption data-rich indications of behavior, tastes, and preferences have increased rapidly thanks to the multiplication of information flows and NICTs (Web, posts and opinions on social networks, data from usage and consumption, geolocation, etc.).
The growth of this data and the commercial potential that it represents necessarily calls for professional functions capable of exploiting it, whatever the format in which it is presented. Within companies, we are witnessing an increase in the technical solutions available to process these large volumes of heterogeneous data (Big data).
In a rapidly changing economic context, relying on figures is reassuring for business decision-makers, especially marketing. They express the need to be based on statistically reliable facts in an environment where the abundance of information and the improvement of the techniques of exploitation make it possible to optimize the company’s economic activity.
By converting these masses of data into commercially exploitable lessons, the data miner facilitates decision-making within companies confronted with big data, which operate in very competitive markets. To discover new growth levers, data scientist course in hyberadad are forced to analyze and optimize what already exists. In this context, the data miner’s profession emerges as a lever and a relay for economic growth.