A Senior Data Scientist role is invaluable for any tech enterprise for that one big leap from technology to leadership. As project leaders, they utilize data to communicate data-driven insights with business stakeholders to create a roadmap for revenue growth.
Their role primarily revolves around the application of machine learning, statistical methods, and exploratory analysis for extracting insights from data.
And so, a Data Scientist’s toolbox contains everything about data visualization, machine learning, deep learning, pattern recognition, data preparation, and text analytics.
A senior data scientist is an end-to-end data scientist. Mahana Mansfield, VP of Science at Deliveroo notes that a senior data scientist basically,
Chanuki Illushka Seresinhe, Head of Data Science at Zoopla and Founder of beautifulplaces.ai explains,
“The role of a senior data scientist is beyond mere technical competence. As advanced experts, they take initiative and learn wider tasks that are beyond data science. The exceptional ones bridge gaps between data science and other teams, communicating complex data science goals to non-technical audiences.”
According to LinkedIn’s Emerging Jobs Report, careers in Data Science are booming and are all set to achieve a growth of $230.80 billion by 2026. The Burning Glass report also finds that demand for senior data scientists is anticipated to grow by 19% in 2026.
Also, worlddatascience says millennials or Gen Z have vast career opportunities in Data Science in the current job market. Not only is the pay great, but also there is exponential demand for future datasets.
The U.S.Bureau of Labor Statistics predicts the growth of the Senior Data Scientist job market at 22% between 2020 and 2030.
As per Glassdoor estimates, the national average for a Senior Data Scientist salary in the USA is $1,42,258 per year with an added compensation between $5,741 – $77,015.
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