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What Is The Hiring Process For Data Scientists At Aditya Birla Group

What Is The Hiring Process For Data Scientists At Aditya Birla Group

Aditya Birla Group (ABG), India’s leading multinational company has strong roots across industries ranging from cement, aluminium and copper, to textiles, chemicals and financial services. The Group Data and Analytics cell (GDNA) of ABG works closely with the businesses to strategise and deliver on its business priorities by leveraging the power of data and analytics. Headed by Deep Thomas, the team works with cutting edge tools and technologies built on a highly scalable and robust big data infrastructure to mine petabytes of structured and unstructured data in seconds. 

The team consisting of data scientists, big data engineers and others, apply high-end applied analytics solutions across B2B and B2C businesses and functions. We got in touch with the company to understand the hiring process of data scientists in the GDNA team which has a centralised structure. Having said that, some ABG businesses also work with vendors directly and sometimes jointly work with vendors with a central analytics team’s supervision. 

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Data Science Skillsets

The company looks out for strong technical hold in data science apart from business orientation and soft skills. Some of the skills that the GDNA team member should have are:

  • Strong business orientation: Understands business processes thoroughly before proposing analytics solutions and is able to understand business reality changes. 
  • Problem-solving: Enjoys problem-solving and has demonstrated a strong aptitude for solving problems in multiple domains. 
  • Applied analytics: Adept at applying modern analytics methods to solving real business problems. 
  • Technical knowledge: Coding skills in R or Python. The candidate should have an analytical bent of mind and understands 1-2 machine learning methods deeply. 
  • Stakeholder management: Ability to manage and present to stakeholders. Strong attitude to bring about change in existing business processes. 
  • Teamwork: Understands that data science productionisation is a team sport and has to be willing to play well with others on the team. 

In terms of the educational background of the candidates, the company looks for bachelors, masters, PhD. They hire candidates ranging from engineers, economic majors, stats majors and data science majors. Talking about the preference they give to educational background and skills while hiring data scientists, the company shared that the ratio of weightage given to skills vs educational background is 70:30.

Ideal Data Scientist At GDNA Team

The company strongly believes in hiring candidates that meet the technical and cultural requirements. One of the key criteria for data scientists at ABG is to have a consultative mindset and willingness to delve into the unknown – both technically and business-wise. For this, they test for the willingness to deal with uncertainty by posing questions about how they deal with uncertainty in the past.

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Some of the key areas defining ideal data science candidates at ABG include: 

  • Willing to team with others to put ideas into production. Willing to go end to end and do what it takes to enable change rather than be only focused on one skill – eg. computer vision. 
  • Willing to continuously learn. Demonstrates curiosity to learn new business domains and new technology domains. 
  • Has a strong research mindset and is willing to find new solutions to tough problems instead of simply lifting and shifting existing solutions. 
  • Has an inclination to accepting outside-in innovation to blend the best outside the company with the best the company itself can create. 
  • Adaptable to unknown business challenges. Willing to be flexible to new business realities and find new ways to add value through digital and analytics.

Interview Process Of Data Scientists At ABG

The data science candidate at the GDNA team of ABG is expected to work in areas such as data visualisation, model building, exploratory data analysis, data clean up, data joins, productionisation of models, presentation to stakeholders, change management at the customer side to enable models to be adopted by business, program management. The interview process is therefore structured to hire a suitable candidate that is a fit around these roles. 

The interview process comprises of following steps:

  • Step 1: Resume screening 
  • Step 2: 45-minute phone screen to determine candidate’s interest and fit into GDNA 
  • Step 3: Coding test 
  • Step 4: Open-ended technical interview 
  • Step 5: Behavioral interview 

The questions are mostly structured around the tool and technique that the candidate is good at. Apart from that, they also carry scenario analysis and coding tests. Sharing the kind of questions that are asked in these areas, the company provided the following examples: 

  • Scenario analysis: Assume we need to open 100 stores in India. How would you go about doing the best locations to pick the stores assuming you have no constraints to data. 
  • Coding tests: What would happen if you change <pick an assumption> in the model? 

Despite following an extensive recruitment process, the company faces challenges in terms of varying skill sets and no standardised testing methodologies. Having said that, the company believes in hiring data science professionals through traditional methods such as consultants, incoming resumes from job portals, referrals and internships. Candidates can apply for data science roles by sending a resume to HR, applying on the ABG portal or contacting any member via Linkedin.

Opportunities for Data Scientist To Grow At ABG

The company provides data science candidates with a lot of opportunities to grow. Some of the opportunities that it provides are:

  • Work with a variety of sectors, both B2B and B2C – manufacturing (metals, cement, chemicals, textiles), fashion retail, BFSI, trading.
  • Opportunity to work on some of the largest datasets in the country around customers, SMEs and vendors. 
  • Learn a diverse set of skills – presentation, program management, change management, stakeholder management.
  • People management – manage vertically and horizontally and influence without authority.
  • IP creation around digital and analytics assets (algorithms, products and platforms). 
  • Interact with the best of India’s and global business leaders and have an opportunity to shape, formulate & execute digital and AI strategy for large global businesses.
  • Learn multiple new techniques in time series forecasting, optimisation, visualisation, computer vision, natural language processing etc. 

On a concluding note, the company advises analytics and data science professionals who wish to carve out a career in the industry to go deep in one business area (eg. BFSI), one business function (eg. marketing, manufacturing etc.) and one technique (eg. time series forecasting) before diversifying. 

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