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What Is The Hiring Process For Data Scientists At MiQ

What Is The Hiring Process For Data Scientists At MiQ

Srishti Deoras
W3Schools

MiQ India, which is at the heart of MiQ’s global operations, consists of three core teams — analytics, tech and data science. For hiring in these teams, they look for candidates that can carry out tasks such as building cutting edge AI/ML-driven products, delivering high-performance programmatic campaigns for clients through advanced analytics-based solutions, and more. To understand the hiring process for data scientists at the company in detail, we got in touch with Anshuman Gupta, VP, Data Science. 

Knowledge And Skill-Set For Data Science Roles

Gupta is quick to add that data science is at the core for MiQ, and therefore, they hire top-notch talent that brings efficiency and knowledge to the table.” We look for knowledge and experience in math, statistics, algorithmic development and coding skills” he said. Additionally, they also look for the ability of a candidate to connect with business stakeholders which is critical both at the initial problem framing stage as well as down the road in “storytelling” the results and enabling the business to put them into action. 

“From a programming standpoint we look for skills around R, Python, Spark/Pyspark and we also leverage platforms like Qubole & Databricks” he said. 



In terms of educational background, MiQ looks for bachelor’s and master’s/PhD in Engineering, Math, Statistics, Operations Research preferably from Tier-1 institutes. 

Gupta further shared that while it is the combination of both educational background and skills that they look for, it varies by the level at which they are hiring. “For more junior roles, there is usually higher weightage to education as most candidates would not have had too much experience developing their skills, whereas for mid-to-senior roles, the skill quotient plus tangible demonstration of those skills to create business value becomes more meaningful” he shared.

Interview Process At MiQ

An ideal data science candidate, according to MiQ, should have these skills:

  • Strong demonstrable evidence of applying data science, analytics, AI/ML techniques to specific use cases within a given business domain
  •  Excellent communication skills to connect with various stakeholders & the ability to navigate ambiguity through a structured and process-oriented approach.
  • Strong alignment with MiQ values which are: Passion, Courage, Determination, Agility & Unity

To ensure that they get the right fit, MiQ follows a stringent interview process consisting of rounds such as initial telephonic screening round, case study round with panel discussions, and interview round with the hiring manager, followed by that of the head of the department. 

While MiQ follows an in-depth process, they often face challenges with candidates not having enough experience in productionising DS/ML-based use cases, inability to navigate ambiguity and uncertainty, a significant gap in the resume and not enough focus on communication and collaboration skills. 

Therefore, to pick the right candidate, they are asked questions around specific use cases that they have worked on the end-to-end, business impact created by them, challenges faced by them from a technical standpoint & how they resolved these challenges, experience of working in an agile/scrum environment, and more. 

MiQ relies on referrals, college alumni groups, apart from working with a few niche consultants to source the talent. Currently, they have multiple openings at the junior Data Scientist – I/II, Sr. Data Scientist level as well as Team Lead – Data Scientist. Interested candidates can apply here.

Growth Of Data Scientists At MiQ

Gupta shares that the data scientist role at MiQ can be broadly classified into two categories —data scientists who work on client-specific projects and data scientists focussing on R&D and product development. From a task perspective, the day to day work ranges from data extraction & preprocessing to exploratory data analysis, model building & validation, communicating and collaborating with business stakeholders, and finally working with the broader tech teams to productionise and deploy the models.

MiQ also ensures that data scientists have multiple avenues of growth available to them. “If someone is inclined towards people leadership then they can grow into the team lead role followed by engineering manager role. Alternatively, on the IC track one can take up the tech lead role on the way to the principal data scientist role. A third growth option is to transition into a more product focussed role through the associate product manager role, which subsequently culminates in the product manager role,” explained Gupta. 

Wrapping Up

While data science recruitment is an extensive process, there are some mistakes that companies can avoid to keep these challenges at bay. Some of the mistakes according to Gupta that companies make while hiring data scientists are not focusing enough on the softer skills like collaborative mindset, ability to navigate ambiguity, bouncing back from setbacks, and more. “At MiQ, we have a very strong values-to-behaviour framework that we use as at all stages of the recruiting process that assess candidates on the 5 value dimensions of Courage, Determination, Passion, Agility & Unity,” he shared. 

For candidates looking out to carve a career in the analytics industry, he advises to Specialise, Specialise and Specialise! — in either a specific industry vertical or a domain of AI/ML such as NLP or computer vision, etc. “And please don’t forget the soft skills!” he said while signing off. 

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