Bangalore, May 0, 2017: Management consultants Zinnov have released a first-of-its-kind study on the Machine Learning expert ecosystem in India, titled “Machine Learning Experts in GICs”.
The study uses Zinnov’s proprietary framework, Zinnov Expert Network (ZEN) to identify the top minds in the area of Machine Learning, analyse key career trends, identify success metrics of Machine Learning Experts, and provide a roadmap and key action points for aspiring experts.
Zinnov’s analysis reveals that there are about 280 Machine Learning experts in GICs, less than 5% of the machine learning talent pool in GICs. Some 75% of these experts are based out of Bangalore centres with Hyderabad and the national capital region coming next in line. The experts average 16 years in experience specific to machine learning, compared to the overall industry average of 6 years.
|The study analysed career trends of these machine learning experts along 4 parameters - Research, Experience, Education and Recognition. Experts across all experience brackets have shown an increased affinity for IP creation over the last decade with special focus on recommender systems, information retrieval, NLP, speech recognition, data clustering etc.|The study indicates that work experience across American/European locations has had a major impact on Machine Learning Experts’ IP portfolio. About 25% of the machine learning experts have work experience outside India, with the majority being in the US. The other factors that play a critical role in strengthening experts’ IP portfolios include a PhD with machine learning specialization and exposure to foreign ecosystems with higher research maturity. For instance, machine learning experts with PhDs from foreign universities have been found to have significantly stronger IP portfolios than their industry peers.
The study also highlights trends across educational backgrounds of the identified experts. Surprisingly only about a third of the current crop of experts have graduated from a Tier 1 university. Irrespective of the graduation launchpad, the experts have elevated through research experience or additional learning resources.
Across experience brackets, there is a distinct shift in responsibilities from hands-on algorithm based research in the initial years to technology and product strategy definition in senior roles.
Says Anand Subramaniam, Engagement Manager & Delivery Head (G.A.P), Zinnov said, “It is imperative to imbibe specific skills like probability and statistics, data modelling & evaluation, distributed computing etc. to be a Machine Learning Expert. Aspiring experts should also get trained on platforms such as Tensor Flow, Theano and plug into international Machine Learning journals by IEEE, IET”
While India still has a long way to go in nurturing machine learning expertise to be at par with more mature technology ecosystems, the future outlook definitely looks positive. GICs are leveraging machine learning experts to drive multiple objectives ranging from exploratory and specific product driven research to developing the organization’s machine learning IP.
“Although Machine Learning as a concept has been in existence since the 50's, its recent surge in application in businesses has made it the talking point and a key focus area across sectors. Today, almost every industry applies Machine Learning in their products, solutions and services. With Machine learning becoming an imperative and a logical step for creating business differentiation, GICs will look at Machine Learning experts to drive the next wave of transformation”, he added.