Analytics Hiring Scenario For Indian Companies Looks Positive, Says Raj Sekhar Of EdGE Networks
This time, for our interaction around analytics hiring scenario in India, we got in touch with Raja Sekhar Pappala, who is the head of analytics at EdGE Networks. The company is in the business of building applications to help organisations acquire the best talent. This HR tech company uses data science and people analytics to ensure workforce transformation. Their productivity tool harnesses artificial intelligence to help solve the toughest talent acquisition and workforce optimisation problems.
Raja Sekhar shares how hiring scenario in Indian companies looks like and the major challenges they face. Raja Sekhar has in the past led several initiatives leveraging data sciences in recommendation systems, semantic search, sensor analytics, image processing, text analytics, among others. His current focus is building machine learning applications for HR technology that deliver significant business impact.
Analytics India Magazine: How does the analytics hiring scenario in Indian companies look like?
Raja Sekhar: It definitely looks positive. In my view, the bulk of analytics hiring happens in larger companies but most of the top tier institutes in the country have aggressively ramped up their analytics curriculum and their study programs, which leads us to believe that analytics hiring is very much on the rise.
AIM: What are the skillsets that companies are mostly looking at while hiring analytics talent?
RS: Skills in analytics have a vast range. It begins with a good understanding of data-for-data pipeline creations, and that’s why SQL, ETL methods with Python and other querying expertise is sought after. Data analytics require a range of skills like statistical knowledge and implementing it using SAS, R and Python, able to form and validate statistical hypotheses, advanced statistical methods of data imputation, and data validation in both descriptive and predictive analytics, among others. Data visualisation using Tableau, Power BI, Qlikview or similar tools comes in parallel as it is a critical aspect of business analyses too. Model-building and knowledge of statistical algorithms also plays a major role in AI hiring. The ability to predict certain critical business parameters takes years of practice to perfect. Big data technologies such as Hadoop and Apache Spark are also a relevant skills in analytics as most of the companies run into terabytes of data or even more.
AIM: The talent gap is often a talk point in the industry. How could it be bridged?
RS: This gap could be bridged by recognising the demand, which is being created for the future. Given that ML and AI will be used in almost any critical business decision-making, ensuring this is an integral part of course curriculums, introducing advanced and relevant programs for those aspiring will definitely help bridge the talent gap. Interactive sessions by real-world practitioners will also generate a serious interest in this booming AI market.
AIM: What are the various initiatives that companies and educational institutions can take to set right the analytics talent flow?
RS: Initiatives could include sessions and webinars conducted by experienced AI practitioners, workshops which offer hands-on expertise in terms of solving real-world problems, live hackathons and active participation in analytics communities.
AIM: What are the challenges in the current education system that stops that growth of analytics talent?
RS: In my opinion, there’s still a void between the way an analytical subject is taught in most schools compared, and its real-world applications. Statistics, applied mathematics and applied econometrics, are examples of an analytical curriculum, which unless studied from a top tier institute or platform may offer very less value, mostly in terms of the way it is used in real world to solve analytical problems. Without a link between its correct understanding and usage, it becomes quite difficult for students to grasp such subjects and later on, they may find it difficult to apply their knowledge in solving business problems.
AIM: What does the typical hiring process look like at your company? What are different stages, processes etc?
RS: Typically, the candidate goes through three to four rounds. It usually starts with a telephonic or Skype technical round, followed by a problem-solving round where the candidate is asked to solve an analytics problem. This is mostly followed by a face-to-face technical and general aptitude round, followed by an HR and management discussion.
AIM: What are the current analytics openings at your organisation? What are the skill sets that you for?
RS: We are always keen on adding talented and enthusiastic people in our team.
AIM: For an analytics professional who wishes to carve a career in analytics industry, what is your advice?
RS: There has to be love for data science. Everything cannot be taught nor is it possible to be accommodated in textbooks. The eagerness to learn the discipline will mostly see one through all hurdles. As mentioned before, apart from rigorous curriculum, trying to solve real world business problems, keeping abreast of analytical technologies and the eagerness to learn from a plethora of information found in white papers, journals, articles on the web is a start.
AIM: What are your thoughts on attrition?
RS: Solving attrition-related problems through analytics is something which most companies have started. Predicting attrition trends, identifying seasonal patterns to attrition, whether it is profitable to hire from top institutes in terms of attrition and cost, who is likely to leave the organisation in the next six months and why, which factors drive attrition in specific grade groups are some of the problems, which revolve around attrition analytics.
AIM: What are the offerings by Edge Networks to help companies acquire right talent?
RS: HIREalchemy is company’s flagship product, which is a cutting-edge talent acquisitionplatform powered by AI and data science. The platform auto-sources the right fit by parsing and analysing both structured and unstructured information from internal database as well as external portals. It eases the process of selection as the platform throws up resume matches by scoring and stack ranking them based on business rules set by the client.
Other key distinctive offerings include Workforce Optimisation Solution, which forms an intelligence layer on top of HR systems and helping in effective organisation building. Whereas another offering, Talent Analytics Suite by the company helps in predicting attrition, forecasting resource demand and enabling fact-based decision making across the HR value chain. Our Workforce Planning solution, on the other hand, helps align talent strategy with business strategy through advanced analytics algorithms. We provide actionable analytics and insights that accelerates business decision making.