Following a hybrid structure, the data science team at Schneider Electric is aligned to various functions such as procurement, manufacturing, logistics etc. The regional teams are governed by a centralised team of experts providing products and solutions to supply chain platforms globally. The company also follows a flat framework that is built to be like a startup — with a completely different workspace — to provide a creative, seamless and fast-moving work environment.
The company follows various traditional and non-traditional ways of recruiting for their data science teams. Apart from hiring through social media platforms and job portals, it also recruits from companies that offer exclusive analytics consulting services, as well as e-commerce players and start-ups.
“We are also active in talent communities to scout for passive applicants. Additionally, we employ young graduates and interns from ace engineering colleges and train them to work on real-time business problems,” said Sanjay Mishra, Vice President, Human Resource, GSC International, Schneider Electric India.
In an effort to strengthen industry-academia partnership, their campus teams are also aligned with the universities to encourage and incorporate analytical training/certification in their curriculum.
What Are The Skills Sets They Look For?
As Madhu Hosadurga Rajanna, Global Director, Analytics at Schneider Electric India shares, they evaluate potential candidates on functional competencies as well as behavioural and cultural fitment aligned to the core values and leadership expectations.
“From a technical standpoint, we look for strong Python or R-Programming skills, a thorough understanding of advanced machine learning techniques such as Neural Networks, PSO etc. Besides functional competencies, we also look for strong analytical and reasoning, structured approach, ‘willing to learn’ attitude and problem-solving skills in a potential candidate,” he added.
In terms of educational background, Schneider Electric prefers BTech or MTech in Mathematics and Statistics subjects from a top league institution. “MBA from an ace management school is a bonus for lateral hiring,” said Madhu.
In terms of what weighs more — educational background or skills — Madhu shares that it is a judicious mix of both that matter while hiring. “While basic knowledge and techniques are acquired through formal education and training/certifications, practical experience is fine-tuned by technical expertise and analytical ability. Beyond education and skills, there is a huge weightage given to the behavioural aspect to hiring high potential candidates,” he said.
Interview Process At Schneider Electric
The company looks for different types of candidates for various positions in data science teams. To get the best talent, it has a thorough interview process that looks for strong analytical skills, understanding of principles in data science, the ability to apply specific techniques to unique business problems and more.
As Madhu shares, the selection process is relatively rigorous and focuses on behaviour-based assessment. He explains the process as below:
- The first step is to understand the breadth and depth of the candidate’s technical capability from the resume by looking at the experience and skills acquired.
- To ensure that all relevant information is obtained they assess against the most critical behaviours for the role in more than one of the interviews – this overlap provides double coverage of the functional competencies and core values/leadership expectations which are most critical to job success.
- Core technical competencies are assessed through case studies. These case studies are developed by internal experts reflecting situations that arise in a real-time business scenario.
- The case studies are assessed by technical experts, further probing their depth of knowledge on machine learning techniques and coding abilities.
He says that while data roles are in high demand and owing to a limited talent pool, finding the right candidate for this role can be tricky and challenging. Therefore, the company endorses multiple interviews across a panel of interviewers to reduce the risk of biased, uninformed or poor decisions.
What are some of the hiring mistakes that companies make while hiring data scientists? “Data Science is one of the most sought-after jobs of the 21st century with very limited and high potential job applicants. Hiring for temporary needs and focussing only technical expertise is one mistake companies do,” shared Madhu.
He further added that at Schneider Electric, they recruit prospects for a longer career and look beyond just technical skills. “We’d like to evaluate their interpersonal skills, leadership abilities, problem-solving skills, understand their professional goals and their openness to learn,” he said.
Data scientists can apply through targeted career sites and job portals. New positions are also reflected on the career page of Schneider Electric India website, apart from social media platforms like Linkedin, which offers a great way to reach out and connect with prospects.
Growth Trajectory Of Data Scientists At Schneider Electric
Talking about the roles and tasks that data scientists should take up, Sanjay said that the data scientist recruit should independently execute innovative programs, and operate in an agile manner, which is a crucial requirement in today’s business scenario. “As a domain and subject matter expert, the candidate should be able to advise customers on certain complex projects, supply chain planning and strategising,” he added.
In terms of the growth trajectory of data scientists, Sanjay shared that at Schneider Electric, three career paths are identified for Data Scientists employed with them.
- First is the Technical path, which leads to an Edison certified expert eventually.
- Second is the Business path, wherein Data Scientists with their business acumen, get the opportunity to work and professionally grow in Business Operations.
- And thirdly the Regional/Functional Digital Leadership path, with the organisation undergoing digital transformation across functions and segments.
It also offers opportunities and exposure in global supply chain projects that enable them to connect and collaborate with global leaders, thus allowing them to drive innovative programs independently. “Such opportunities not only help them get recognition but also leads them to fast-track growth based on successful deliveries and outcomes,” added Sanjay.
Advice For Professionals Willing To Carve Career In Data Science
Madhu shared that whether you are a seasoned analytics professional or a fresh graduate looking to break into data science, one must develop a profound knowledge in the field and concentrate on continuous learning every day. He advises:
- Analytics is just a tool to solve business problems. So, develop skills in identifying and resolving business problems.
- The technological landscape is rapidly evolving. It becomes even more important to stay curious and focus on continuous learning to avoid becoming redundant.
- Career isn’t limited to technological or coding skills. Even though programming skills are in high demand currently, overall people management skills, leadership qualities must be nurtured to progress in career.
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Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.