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What Is The Hiring Process For Data Scientists At TheMathCompany

What Is The Hiring Process For Data Scientists At TheMathCompany

Srishti Deoras

Data scientist is one of the most in-demand jobs despite the ongoing pandemic. While there are openings for data science roles in many firms, they still face challenges in terms of scarcity of the right talent, communication skills, cultural fit and compensations. But there are companies such as TheMathCompany that are looking for more than just checking these boxes. 

What are the skills that they are looking for? As Ashish Sam, Senior Partner – People & Operations at the TheMathCompany notes, a data scientist and engineer must always be able to think ahead in terms of what the customer needs, even if the customer is unaware of it. Just delivering what the customer asks for, will not move the needle. 

“What will keep data scientists and data engineers ahead of the curve is the willingness to learn, structured thinking and the ability to break down problems,” he says.



In terms of tools and technologies, the company is looking for someone conversant in big data tools like Hadoop, Hive, Sqoop, etc., programming languages like Python and Scala. “It’s good to have an exposure to cloud technologies like AWS / Azure / GCP and Spark framework,” he added. 

Outside the tools and technical checklist, TheMathCompany is looking for attributes such as: 

  • Aptitude – Is the person able to think factors/data elements/variables.
  • Ability to break down a problem – How do they go about solving a problem, what’s their thought process.
  • Logical thinking – Are they considering the critical ideas and facts associated with a problem and consistently using reasoning to arrive at a conclusion.

An ideal candidate at TheMathCompany is expected to pose cross-discipline knowledge of the current technologies, statistics & data science algorithms, effective communication skills and deep discipline expertise in one of the functional areas such as coding, business intelligence, big data technologies and ML algorithms.

“We nurture full-stack experts who are well-versed in either data science or data engineering, while displaying a basic working knowledge of the other, alongside domain knowledge – wielding T-skilled expertise,” said Ashish. 

What Are The Educational Requirements 

While most of the hires at TheMathCompany are engineers, they are keen to hire talent from varied backgrounds such as mathematics, statistics, economics, psychology, among others to bring refreshing perspectives to the table. 

“In fact, one of our senior team members who does not have a textbook analytics pedigree and is from an Economics background leads client engagements today. She’s proof of how a problem-solving mindset and being open to pick up new skills, learn and unlearn is what matters while hiring candidates, rather than being a stickler for specific educational backgrounds,” he said. 

Do they weigh skills over education? “We believe education as a foundation is non-negotiable. Having said that, we believe in skills over pedigree and consider it to be of utmost importance while hiring,” said Ashish. 

To keep their team abreast of new developments, they even have an in-house growth accelerator cell called Co.ach. It offers a wide array of training programs in the latest tools, technologies and techniques in the industry, bridging any gaps and making sure that talent can effectively execute client projects.

Interview Process At TheMathCompany

The analytics team at TheMathCompany is a mix of data science, data engineering, product engineering experts, coupled with consultants and SMEs. “Our hiring process is therefore not defined to find the exact profile but identifying folks who have the right attitude, growth mindset and are a good culture fit,” said Ashish.

The interview rounds are therefore three-fold — problem-solving round, case study or technical round and culture fit round. He further explained that the first two rounds involve testing employees with a wide range of questions centred around evaluating their business understanding, workings and application of algorithms, know-how of tools and technologies, communication, problem-solving and stakeholder management skills.

The third round is used to gauge softer aspects such as style of working, decision-making, management, and evaluate their EQ, grit, level of ownership, if values and traits resonate with their culture, and so on.

The hiring process is quite extensive to ensure that they are hiring the right candidate. It includes:

Sourcing

  • Sourcing relevant resumes using portals
  • Social media recruiting
  • Networking, cold calling, headhunting
  • Employee referral program

Screening

  • Screen resumes based on defined criteria
  • Recruiter first connect with screened candidates via email or phone call
  • Introductory Call – MathCo pitch, role description, candidate assessment

Scheduling

  • If shortlisted, schedule interview with a panel
  • If the profile is shortlisted, agree upon panel and candidate availability, mode of interview.

While some of the traditional ways of hiring at TheMathCompany are through job portals, employee referrals, and vendors, they also engage through non-traditional channels such as career fairs, social media channels such as LinkedIn and Facebook, conducting Hackathons and more.

The company is currently looking for data scientists, data engineers and product engineers with 2+ years of experience. Candidates can check their careers page or send their resumes to careers@themathcompany.com. 

Roles and Responsibilities Of Data Scientists At TheMathCompany

Data scientists at TheMathCompany are expected to perform tasks such as data migration, pipeline creation, data wrangling, machine learning, automating pipeline, creating consumable analytics products, and more. 

Career path role at the company involves: 

  • Working on real-world problems and execution aspects focused on delivering results.
  • Understanding problems and domain-specific challenges that clients face.
  • Breaking down problems into smaller components and designing a solution around it.
  • Leading and managing a team of analysts to solve client problems.
  • Proactively participating and leading non-technical activities that are geared at building the organisation, and helps employees in honing their soft and leadership skills, while offering networking and team-bonding opportunities.

“At TheMathCompany, we offer data scientists, data engineers and product engineers an opportunity to take complete responsibility and ownership of their work. We offer numerous opportunities for them to spread their wings and go from execution/operational responsibilities to leading engagements on their own,” he said. 

Apart from providing with ample opportunities, the company also focuses on the well-rounded training experience of the candidate

“With endless learnings and growth possibilities at their disposal, we also ensure employees do not let their work-life balance take the backseat, whether it’s through participating in our in-house wellness activities or other means,” he added. 

Mistakes To Avoid While Hiring Data Scientists

Many companies make the mistake of going by a common rulebook or being far too flexible with their search filters. It’s essential to identify what is non-negotiable and what can be taught while hiring. “We have our own rulebook, to meet our hiring needs, such as targeting candidates from specific yet diverse education backgrounds, stressing on not just the coding aspect but assessing candidates on math and stats knowledge, accessing the business understanding, and more,” said Ashish.  

Finally, to those looking to get a job in the analytics profession, Ashish says that it is crucial to unlearn old skills and learn new skills every 2-3 years. Some of the other pointers that he advises to keep in mind are:

  • Get better at problem-solving – and honing your analytical thinking ability.
  • Get better at applying concepts in real-world scenarios and not just understanding them.
  • Be open to picking up any skill (technical or non-technical).
  • Grasping the business of your customer/client is critical for overall success. Diving into the data and the math behind the business problem is an essential part of enabling client success stories.
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