Artificial Intelligence (AI) is everywhere around us. It has already been widely integrated into our daily lives by the smartphone in our pocket and the Apple Watch on our wrist. This technology has become an integral part of our everyday lives, and we are now interacting with it regularly. We are already living in the age of AI, which is projected to continue growing at an exponential pace. In turn, the number of job roles and the type of skills necessary to support AI initiatives at the enterprise is also increasing. The days of everyone calling themselves a “Data Scientist” are almost over, so let’s take a look at the various roles within AI.
One pivotal role when discussing AI is the role of Software Engineer. At its core, AI requires data to perform – and without systems to capture this data (consistently and reliably), no algorithm or fancy model will provide valuable insights. Software Engineers are the first line of AI – developing tools and systems to make it easier to build machine learning and deep learning-based algorithms. Social Media apps, sensors, mobile apps, Internet of Things (IoT), analytics tools all have the potential to capture this valuable resource. These software applications (internal and external) have the power to make a new AI initiative within a corporation successful or painfully troublesome.
If producing and capturing data is pivotal, then finding it and accessing it is indispensable. At the most basic level, the Data Engineer is responsible for analyzing and cleaning the data gathered from the various systems and tools used across an ecosystem. The Data Engineer is the all-around data specialist that prepares data and ensures that it can be consumed and utilized within the organization. By extracting information from various systems, transforming/cleaning data, and combining disparate sources to form a functioning database – the data engineer is the “hidden jewel” in AI. Often these individuals need to have an in-depth knowledge of the business processes that enable them to find hidden data treasures.
Moving from simple data to predictive models is where the Machine Learning (ML) Engineer shines. The ML Engineer is responsible for developing and training models and algorithms using advanced statistical techniques and data science skills. They identify patterns in historical datasets, find the most influential factors and attributes to a particular outcome, and experiment with feature engineering to improve these models’ scalability and deployment. A discounted responsibility of the ML Engineer is related to business consumption. If the predictive model has exceptional predictive power, but business users are not utilizing its recommendation – “well if an algorithm makes a prediction in the woods and no one hears it…”. The ML Engineer must create the most accurate model possible using their advanced analytical skills and the best method for business users to trust and use the insight to run and optimize their business results.
AI Business Strategist
We can now capture data, access data, and even make unique predictive models, but just because it can be built – should it be built? The AI Business Strategist is an often-neglected role when enterprises are instituting AI for the first time. This role is less about the technical aspect of AI and more about the softer side of AI. The AI Business Strategist should be a senior individual who understands what AI is capable of (Art of the Possible) and recognizes the business impact it can have across an organization (Transformational). They know the business goals and can garner executive sponsorship to experiment with minimum viable products (MVP). They have the business acumen to identify and prioritize the first AI projects an organization should pursue based on their analytics maturity and data fluency. In the simplest terms, an AI Business Strategist can help an organization launch successful AI initiatives that can demonstrate positive ROI.
When considering the ongoing progress of AI within the enterprise, it’s essential to take a step back and look at the big picture. AI is the latest technological advance that’s changing the way business is being conducted today. Companies are leveraging AI across a broad spectrum of functions, enabling them to provide a superior customer experience and deliver a higher return on their investment. Organizations must understand how AI will impact many of the current jobs and ensure they consider all the roles that will enable a successful AI implementation.
Originally posted on the Catalytics Blog: https://catalyticsconsulting.com/what-are-the-different-job-roles-within-artificial-intelligence