AI - Powered Careers: Navigating Opportunities in Data Science & Analytics

Authored by Hariom Seth, Founder, Tagglabs

Most companies are applying data driven decision making to boost the organisation's productivity. An increasing number of companies are utilising big data and predictive analytics. This has increased the demand for skilled professionals in AI, more specifically data science and data analytics. While most jobs offered in data science/analytics are from the IT services/consultancy and software development industry. Industries such as healthcare and investment management too require data analysts/scientists. AI is a vast field encompassing various genres. These fields require technical and nontechnical job roles which are as follows:

Career progression in Technical jobs roles:

Entry Level —-> Mid Level —-> Senior level

1. Data Analyst:Data analysts interpret and clean collected data, identifying trends crucial for strategic business decisions. They utilise SQL, R, SAS, and visualisation tools like Power BI and Tableau. Strong communication skills are essential as they convey findings to non-technical teams. Typically beginning with internships, they progress to entry-level positions, then to senior roles involving team management and project planning.
     
2. Data engineer:They are like software engineers specialised in data, gathering data from diverse sources to construct a data warehouse accessible to the entire organisation. They gather, manage, and transform raw data into usable formats for data scientists and analysts. These systems guarantee seamless data flow from multiple sources to the data warehouse or data lake, ensuring uninterrupted access for end-users without loss or corruption.
   
   
3. AI engineer: In this role the individual utilises data to develop models capable of predicting or making decisions autonomously, without explicit programming for the task. The responsibilities of an AI engineer include: understanding the business challenge, crafting a solution, coding the model, and deploying it.
   
   
4. NLP engineer: They are AI engineers choosing to specialise in natural language processing. They design. They design computer systems that enable computers to understand, interpret and generate language. They primarily work on chatbots and voice assistants. They work on a combined knowledge of computer science, artificial intelligence and linguistics that help humans and machines communicate.   
   
   
5. CV engineer: These are AI engineers choosing to specialise in Computer vision. These engineers help machines understand the visual world around them by interpreting algorithms that understand digital images. They train computers to do tasks including object detection, image classification, and facial recognition. They work on specific tasks like object detection, image segmentation, and 3D reconstruction.
     
6. Data Scientist: Data scientists focus on creating algorithms and predictive models for data analysts, aiding organisations by developing tailored methods and tools for data extraction and task automation. Interns start by cleaning and preparing data, learning software like SQL, Excel, Python, and R. Those excelling 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 long-term project planning. Data scientists typically earn more than analysts, with analysts often advancing to data scientist roles.

Non- technical job roles:
 

1. AI product manager: this role is right at the intersection of business and technology. AI PMs work with stakeholders to understand their demands from a product, the product goals, product features and the market. They also work with the developers to build AI products that fulfil customer needs. They act as a bridge between the business and the technical team. They don't necessarily code but have a very good understanding of various AI concepts.
   
   
2. AI Sales Executive: A core member of an AI-focused sales team, is responsible for selling AI products and services to the right customers. They require a deep understanding of the AI tools and services they offer. They are the trusted partner of leading innovators and work on growing their relationships and winning new work for the growth of the organisation. Their main goal is to understand the needs of potential customers and accordingly offer AI solutions to the customers. 
   
   
3. AI Ethicist: they bring to light problems that rapid AI innovations can bring to the society as a whole. They ensure that as AI is developed and deployed it is done so responsibly. They deal with AI and its implications on humans such as:
1. Preserving human rights
2. Building trust in AI systems
3. Promoting responsible AI research and innovation
4. Understanding and addressing the economic impact of AI
5. Dealing with damage done by AI

DISCLAIMER: The views expressed are solely of the author and Adgully.com does not necessarily subscribe to it.