Jobs in finance requiring AI skills are on the rise, and here are some examples



The financial sector is banking on AI and creating new jobs to bridge the gap.

Traditional financial institutions and fintech start-ups are looking for more candidates specializing in artificial intelligence, machine learning and data science. According to Bloomberg reports and data from LinkedIn, jobs requiring these skills in the financial sector have increased by almost 60% in the past year.

According to data from Glassdoor, “some of the most common jobs in AI and finance are for machine learning engineers and data engineers, among other highly specialized roles in software engineering,” said Daniel Zhao, senior economist. Glassdoor, at CNBC Make It. “We’re also seeing job postings for workers who can help navigate the AI ​​landscape, including consultants and researchers. As companies lay the groundwork for their AI functions, we’re seeing employers hire more experienced candidates to lead these new teams. “

However, not all new business functions are rooted in IT or engineering. For example, chatbot editors (those who write conversational responses to technical questions customers ask about website “chat” features), product strategists, and technical sales reps are also in demand, Zhao says. . Those with a background in business or communication may be better suited for these roles.

And workers who already work in finance but want to learn more about AI have a head start, Zhao says. “Their expertise in business and finance is a great way to differentiate themselves in a hot technical field.”

Here’s a look at some of Glassdoor’s current financial services AI job openings, along with the job site’s estimated salary range for each.

Senior Experience Designer, Bank of America

  • Job Description: Work on creating user-centric experiences for digital platforms including mobile apps, responsive web, ATMs, artificial intelligence and other emerging technologies.
  • Minimum qualifications: bachelor’s or master’s degree in design
  • Estimated salary: $ 112,000 to $ 123,000

Data Scientist, Morgan Stanley

  • Job Description: Analyze data and develop predictive models for various use cases within sales and marketing, such as sales targeting and segmentation, lead generation, and product recommendation.
  • Minimum qualifications: master’s degree in computer science, statistics, applied mathematics or relevant field
  • Estimated salary: $ 127,000 to $ 184,000

Senior Trade Credit Product Manager, Capital One

  • Job Description: Lead teams of designers, engineers, data scientists and analysts to define product strategy and develop, launch and improve products and services. Apply technologies like automation, machine learning, artificial intelligence, and predictive analytics to reinvent the way Capital One manages risk.
  • Minimum qualifications: Bachelor’s degree in computer science or engineering
  • Estimated salary: $ 65,000 to $ 112,000

IA backend engineer, JP Morgan

  • Job Description: Design and build database systems and machine learning platforms to transform business operations. Develop scalable, fault-tolerant back-end systems that process data and meet machine learning demands.
  • Minimum qualifications: bachelor’s, master’s or doctorate in computer science or a related quantitative field
  • Estimated salary: $ 89,000 to $ 111,000

Learn AI without a computer science degree

Professionals with an engineering background will have a growing field of opportunities in the field of finance. For those without a STEM background, however, the ability to adapt and acquire such skills will be crucial across a wide range of professional functions. “With so many online courses and boot camps available, it has never been easier to learn AI and machine learning skills that can enhance your career,” Zhao said.

LinkedIn offers online courses to learn skills such as cloud computing, artificial intelligence, and analytical reasoning. Hundreds of universities around the world offer free online courses – or partially free – many of which fall into the categories of computer science, math, programming, and data science. In addition, training academies and boot camps have sprung up to bridge the gap between working professionals who want to acquire technical skills that can translate into a new role or improve their current job.

The question of whether workers should seek out these opportunities, or whether they will be encouraged and provided by employers, remains unanswered.

“It is important that companies continue to invest in their employees so that they improve and re-qualify their employees to keep them up to the roles in demand,” said Feon Ang, vice president of talent solutions and learning in Asia. Pacific on LinkedIn, at CNBC’s “Capital Connection”. “At the same time, people need to keep investing in themselves and have a growth mindset.”

A recent report from IBM suggests that employers recognize the growing need to retrain workers – around 120 million worldwide over the next three years – due to AI and automation. However, report executives point out that soft skills such as flexibility, time management, and the ability to work in a team are more important skills than STEM technical knowledge or basic computer and software / application skills.

Hiring adaptable professionals and investing in data science, engineering and AI training programs can help companies drive technological innovations from within, the IBM report suggests.

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