Written by Hariom Seth, Founder of Tagglabs
Most of the companies are implementing data-driven decision making to increase the productivity of the organization. An increasing number of companies are using big data and predictive analytics. This has increased the demand for skilled AI professionals, especially in data science and data analytics. Most of the jobs offered in the field of data science/analytics are from the IT services/consulting and software development sector. Industries like healthcare and investment management also need data analysts/scientists. AI is a vast field encompassing various genres. These fields require both technical and non-technical roles which are as follows:
Career progression in technical professions:
Entry Level —-> Intermediate Level —-> Advanced Level
- Data Analyst: Data analysts interpret and clean collected data, identifying trends that are critical to strategic business decisions. They use SQL, R, SAS, and visualization tools like Power BI and Tableau. Strong communication skills are essential to convey findings to non-technical teams. They typically start as interns, then progress to entry-level positions, and then to management positions involving team management and project planning.
- Data Engineer: They are like software engineers specializing in data, collecting data from various sources to build a data warehouse that is accessible to the entire organization. They collect, manage, and transform raw data into formats that can be used by data scientists and analysts. These systems ensure a smooth flow of data from multiple sources to the data warehouse or data lake, ensuring uninterrupted access to end users without loss or corruption.
- AI Engineer: In this role, the individual uses data to develop models that can predict or make decisions autonomously, without explicit programming for the task. Responsibilities of an AI engineer include: understanding the business challenge, developing a solution, coding the model, and deploying it.
- NLP Engineer: These are AI engineers who choose to specialize in natural language processing. They design. They design computer systems that allow computers to understand, interpret, and generate language. They mainly work on chatbots and voice assistants. They work on a combined knowledge of computer science, artificial intelligence, and linguistics that helps humans and machines communicate.
- Engineer CV: These are AI engineers who choose to specialize in computer vision. These engineers help machines understand the visual world around them by interpreting algorithms that understand digital images. They train computers to perform tasks such as object detection, image classification, and facial recognition. They work on specific tasks like object detection, image segmentation, and 3D reconstruction.
- Data Scientist: Data scientists focus on creating algorithms and predictive models for data analysts, helping organizations by developing bespoke methods and tools for data mining and task automation. Interns start by cleaning and preparing data, learning software like SQL, Excel, Python, and R. Those who excel may receive pre-placement offers and become junior data scientists, working closely with seniors and engineers. Progression from junior to senior data scientist involves managing teams and planning long-term projects. Data scientists typically earn more than analysts, with the latter often progressing into data scientist roles.
Non-technical positions:
- AI Product Manager: This role sits at the intersection of business and technology. AI product managers work with stakeholders to understand their requirements for a product, product goals, product features, and the market. They also work with developers to build AI products that meet customer needs. They act as a bridge between the business and the technical team. They don’t necessarily code, but they have a very good understanding of various AI concepts.
- AI Sales Manager: A key member of an AI-focused sales team, responsible for selling AI products and services to the right customers. Must have deep knowledge of the AI tools and services they offer. Serves as a trusted partner to key innovators and strives to grow their relationships and secure new business for the organization’s growth. Their primary focus is to understand the needs of potential customers and propose AI solutions to customers accordingly.
- AI Ethicist: They highlight the problems that rapid innovations in AI can bring to society as a whole. They ensure that the development and deployment of AI is done responsibly. They address AI and its implications for humans, including:
- Preserving human rights
- Building Trust in AI Systems
- Promoting responsible AI research and innovation
- Understanding and managing the economic impact of AI
- Dealing with the damage caused by AI
DISCLAIMER: The opinions expressed are solely those of the author and Adgully.com does not necessarily subscribe to them.
