Upgrade & Secure Your Future with DevOps, SRE, DevSecOps, MLOps!

We spend hours on Instagram and YouTube and waste money on coffee and fast food, but won’t spend 30 minutes a day learning skills to boost our careers.
Master in DevOps, SRE, DevSecOps & MLOps!

Learn from Guru Rajesh Kumar and double your salary in just one year.

Get Started Now!

The highest paying data science jobs in finance

Source – https://www.efinancialcareers.com/

If you’re looking for a data science role in financial services, and are expecting to earn an enormous salary and bonus, you may well be disappointed. Data science roles in financial services come in a variety of forms and some pay a lot better than others. 

A new salary and bonus survey from recruitment firm Octavius Finance highlights the discrepancies. Not only are some roles more lucrative, but some types of employer are more generous too.

Octavius Finance splits data science jobs into five categories, defined as follows:

  • Data strategists and relationship managers: People who researching new data sources and manage vendor relationships.
  • Data analysts: People who engage in exploratory data analysis to make data consumable.
  • Data engineers: People who clean and organize data and build data pipelines
  • Data scientists: People who harvest Alpha, combine alpha signals, engage in systematic backtesting and machine learning.  
  • Quant researchers: People who building systematic trading models, strategies and trading signals

As the pay charts below show, data scientists and quant researchers are by far the best paid in London. Moreover, hedge funds are far more lucrative places to work as a data scientist than investment banks. 

Quant researcher salaries and bonuses are shown in the final chart on their own. Octavius director Natalie Basiratpour says hedge fund bonuses aren’t included because they vary widely depending upon factors including the size of the team, assets under management and the performance of the signal. 

Related Posts

What is Data Pipelining Tools and that are the Different Types of Data Pipelining Tools?

Introduction to Data Pipelining Tools Data pipelining tools are an essential part of modern data management processes. As companies collect more and more data, they need to Read More

Read More

What are Data Engineering Tools?

Introduction to Data Engineering Tools Data engineering is a crucial component of the data lifecycle that involves collecting, transforming, storing, and managing large datasets. With the increase Read More

Read More

What is a data science platform?

Introduction to Data Science Platforms Data Science Platforms have revolutionized the way businesses operate by providing a comprehensive suite of tools for managing and analyzing large volumes Read More

Read More

What are Data Analytics Tools and Why are Data Analytics Tools Important?

Introduction to Data Analytics Tools Data analytics tools are software solutions designed to collect, process, and analyze large sets of data to extract valuable insights. With data Read More

Read More

What is Data Science Platform and Why Data Science Platform is important?

Introduction to Data Science Platforms In today’s data-driven world, businesses are collecting and processing vast amounts of information to gain insights, make informed decisions, and stay ahead Read More

Read More

GET RECRUITED: TOP DATA SCIENCE JOBS TO APPLY THIS WEEKEND

Source – https://www.analyticsinsight.net/ Data science is an essential part of any industry today, given the massive amounts of data that are produced. Data science is one of Read More

Read More
Subscribe
Notify of
guest
0 Comments
Oldest
Newest Most Voted
0
Would love your thoughts, please comment.x
()
x