New-age careers in Maths – The Hindu

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In an era where technology and data analytics are transforming every sector of the economy, Maths has emerged as a critical pillar in driving innovation and efficiency. From Artificial Intelligence and Machine Learning to financial markets and autonomous systems, the application of mathematical principles is pivotal in developing cutting-edge solutions and making informed decisions. Here are six career options that blend mathematical expertise with industry-specific skills

Algorithmic Trader: Algorithmic trading has revolutionised the finance industry by using sophisticated mathematical models and computer algorithms to execute trades at unprecedented speeds. These models help predict market movements and capitalise on fluctuations in milliseconds. This role requires a deep understanding of both Maths and Finance to create algorithms that can consistently outperform the market under various conditions. An algorithmic trader uses advanced calculus and statistics to model and predict market behaviour and understand the intricacies of different financial markets and instruments, guided by mathematical principles such as probability and risk analysis.

AI Ethics Officer: ensures that AI systems are developed and deployed in a manner that adheres to ethical standards and societal norms. They employ Maths to identify and reduce biases in AI algorithms, ensuring machine-made decisions are fair and transparent. They create frameworks using statistical models and ethical algorithms to detect and correct biases, and utilise mathematical reasoning to align AI practices with global data protection and privacy standards.

Autonomous Vehicle System Analyst: Also known as self-driving cars, autonomous vehicles use a complex mix of Maths, Computer Science, and Engineering to navigate safely and efficiently without human intervention. An Autonomous Vehicle Systems Analyst develops and refines the algorithms that allow these cars to “see” and “decide”. They apply principles of linear algebra and differential equations to design systems that can predict and adapt to dynamic environments and enhance autonomous algorithms with machine learning techniques, requiring strong statistical analysis and optimisation skills.

Cryptocurrency Analyst: uses mathematical models to evaluate the stability and potential of various digital currencies, assess market trends, and advise on investment strategies. They use probability and statistical inference to assess the chances of different outcomes and employ statistical analysis and predictive modelling to study market trends and make informed investment decisions based on data.

Digital Twin Engineer: creates digital versions (or twins) of physical systems ranging from a car engine, a building, a manufacturing line, or even a city’s water supply network. Using these digital twins, they predict what will happen in the real world under different conditions without ever touching the actual system. These engineers use Maths to describe every aspect of the digital twin, from geometry to simulate shapes and sizes of physical objects, to calculus and algebra to model how things change over time.

Operations Research Analyst: Vital in industries ranging from logistics and transportation to healthcare and defence, they use mathematical models and algorithms to optimise operational efficiency, reduce costs, and improve service delivery. Their work involves solving some of the most complex decision-making by applying a mix of mathematical, statistical, and computational techniques.

The integration of Maths into these high-demand roles is not just about applying known formulas to solve equations; it’s about using Maths to innovate, predict, and optimise in a rapidly changing world.

The writer is the founder and CEO of Bhanzu, a Maths education platform.

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