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Senior Data Scientist

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Who is a senior data scientist?

 

SEnior data scientists are analytical experts who utilize their skills in both technology and social science to find out about the trends and manage data. A data scientist’s role combines the knowledge from computer science, statistics, and mathematics.

 

They also analyze, process, and model data which is then interpreted to create actionable plans for companies and organizations.

 

What does a senior data scientist do?

 

A senior data scientist oversees the activities of the junior data scientists and provides information on statistical and mathematical concepts for the broader Data and Analytics department.

 

The senior data scientist applies and inspires the adoption of advanced data science and analytics across the business. The data scientist also synthesizes and leverages the business’s dataset and data to enhance the business’ capabilities for overall goal achievement.

 

Job brief

 

We are searching for a strategic and inquisitive senior data scientist to develop and run data-centered projects. In keeping up with this aim, the data scientist will be required to outline work requirements, assign tasks to the team and monitor their performance. You should also harness your mystery of data science to consult on various aspects of these and other projects.

 

To be a successful senior data scientist, you must be able to utilize data to ultimately inform and promote the company’s expansion. A top-notch senior data scientist will have a prominent role in the development of the junior team.

 

Duties and Responsibilities:

 

The duties and responsibilities of a senior data scientist can be provided as follows:

  • Formulating, managing, and suggesting data-driven projects that are geared at furthering the business interest
  • Cleaning and collating data from various origins for later use by junior data scientists
  • Delegating tasks to a junior team of data scientists in order to realize the successful completion of projects
  • Selecting and employing advanced statistical procedures to ensure there are actionable insights
  • Producing and disseminating non-technical reports that provide an in-detail outlook on the success and limitations of each project.
  • Suggesting ways in which the insights that are obtained will be helpful in forming new business strategies
  • Cross-validating of models to ensure their generalizability.
  • Staying informed regarding the recent developments in Data science and adjacent fields to ensure that outputs are always relevant.

 

Key requirements

 

The key requirements of a senior data scientist can be provided as follows:

  • An advanced degree in data science, statistics, computer science, or a similar field
  • In-depth understanding of SQL
  • Extensive experience as a data scientist
  • Proficiency in R or python where the former will be more preferred.
  • Competent in machine learning principles and techniques
  • Outstanding supervision and mentorship decisions
  • Capacity to foster a healthy, stimulating working environment that allows a better teamwork experience
  • An experience in the history of devising and overseeing data-centered projects
  • Ability to relay layman’s terms such that they can be used to inform business decisions.
  • Compliance with prevailing ethical standards.

 

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