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What Is The Hiring Process For Data Scientists At ThoughtWorks?

What Is The Hiring Process For Data Scientists At ThoughtWorks?

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While data is the lifeblood of the modern digital business and enables leading enterprises to gain the insights needed to outpace rivals, this is also a world of technological dead ends and broken promises. ThoughtWorks believes that much of today’s legacy infrastructure makes it harder to turn data into intelligence, and one such challenge is finding the right data science candidate. 

“Data science practitioners are in high demand in today’s market. This makes the availability of the right talent suited to our specific business needs, limited,” says Savita Hortikar, head of recruitment at ThoughtWorks.

Interview Process At ThoughtWorks

ThoughtWorks believes in using a healthy mix of employee referrals, inbound and outbound applications while hiring for data science roles. “We also leverage recruiting platforms that use AI and ML tech to source candidates,” said Hortikar. 



For data practice — which is centralised and non-hierarchical  — they look for skills such as math, statistics, machine learning, deep learning, natural language processing, operational research and product experience. “We also look for a passion for data science and analytics alongside a willingness to learn and explore the data space because we believe skills can be taught but passion cannot,” she said. She further added that ThoughtWorks’ Data Practice extends beyond the work they do for customers and therefore look for a passion for technology to help change the world with software. 

In terms of educational background, they look for people with knowledge or experience in math, statistics, computer science — with degrees ranging from Bachelors in Engineering, MCA or Masters and PhD.

“Having said that, ThoughtWorks always has and will continue to hire based on skill and passion for technology, which means we value skill over educational degrees,” said Hortikar. 

The steps involved are: 

  • A technical phone interview follows a recruiter’s phone screening round.
  • As a next step, the candidate is given a remote assignment. This is followed by another technical interview that delves into the assignment in detail.
  • The third technical interview discusses the candidate’s technical breadth and depth depending on their experience level.
  • This is followed by the cultural fitment round and an interview with the function heads.

“We look at the candidate’s relevant experience when hiring for this practice. We enquire if the candidate has a strong hands-on project experience coupled with a strong conceptual understanding of math and statistics. Also important is the candidate’s technical grasp of concepts like Machine Learning, Deep Learning, Natural Language Processing etc. We also appreciate varied experience across multiple domains,” said Apoorv Singhal, senior recruiter at ThoughtWorks.

See Also

ThoughtWorks is currently hiring Data Scientists and Data Engineers for their data practice. Interested candidates can apply through ThoughtWorks career page, Linkedin and Glassdoor jobs posting page.

Roles And Responsibilities Of Data Scientist At ThoughtWorks

At ThoughtWorks, data science practitioner has the opportunity to:

  • Understand the business challenges and goals of a client from various domains
  • Formulate data analysis and create a model to meet their needs and help in decision making.
  • Create advanced analytics models using statistical and machine learning methods.
  • Work with software developers and solutions designers to deliver analytics-driven solutions.
  • Represent the company in various online and offline forums such as events, conferences, meetups and more.
  • To be able to work in a dynamic, collaborative, transparent, non-hierarchical, and ego-free culture where talent is valued over a role title.
  • Focus on passion rather than a predetermined one-size-fits-all plan.

On a concluding note, Singhal shared that we make sure that we have properly defining attributes required for the particular job role. “We spend a lot of time on hands-on assessment, and we exhaustively list out the attributes needed for a job. We also invest time to understand candidates’ career aspirations when we match them to data science job profiles,” he said while signing off.

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