What Is The Hiring Process For Data Scientists At Bridgei2i

With strong AI and analytics operations, Bridgei2i has over 600 data scientists forming the backbone of the team. As the company focuses on delivering AI-powered transformation, they rely on data science, technology, and business applications to provide the best outcome — for which the data science team plays a key role. 

To drive a large data science team, the company fosters an open and people-driven work culture while encouraging collaborative and inclusive decision making across teams to nurture a problem-solving ecosystem. To understand in detail about their data science teams and how they hire data scientists in it, we got in touch with Preeth Joseph, Director – Talent and Strategy, BRIDGEi2i, for this week’s column.

Data Science Skill Sets

As Preeth shares, at Bridgei2i, they generally shortlist candidates skilled in technology, data science, or business applications. Apart from this, there is a strong focus on personality fit as they believe that passion and attitude go longer than knowledge and skills when it comes to screening candidates.

In terms of educational background, while Bridgei2i looks for candidates with a strong academic background in a quantitative discipline, it is the business problem-solving, analytical, and customer-centric attitude they prioritise the most. Apart from engineers and statisticians, they are also open to candidates with different backgrounds if they exhibit a keen passion for data-related problem-solving. 

At Bridgei2i, data scientists primarily use artificial intelligence and ML-techniques to solve analytical problems for clients. An integral part of the AI Innovation Labs involves the development of advanced AI accelerators. “Our data scientists often alternate between various roles – that of strategists, inventors, or storytellers!” she said. 

Talking about how an ideal data science candidate should look, Preeth is quick to add that a perfect candidate should be a team player who is good at solving data analytics problems and finding new innovative ways of solving business problems. “Ability to work well with a diverse set of people is crucial since strategising and collaborating across teams is a big part of what we do, and how we deliver best in class solutions to our clients,” she added. 

Data Scientist Hiring Process

A typical hiring process at BRIDGEi2i consists of multiple rounds of assessments, which usually begins with an initial screening of the resumes followed by numerous rounds of interactions and interviews. The interview round involves questions around their skill sets, prior experiences, and domain expertise. As mentioned earlier, considerable stress is applied to match applicants’ personalities with their ecosystem and culture!

Talking about the challenges while hiring, Preeth said that while there’s no dearth of candidates for data science positions, one of the major challenges they face is the candidate’s lack of hands-on experience with the technical aspect of their projects.

“One of the issues we face while hiring is that candidates do not always have all the skills needed to work and excel in the team successfully. Determining the right cultural fit may also take some time,” shared Preeth. He further added that they overcome these gaps with structured programs such as LeGo and SCaLa to nurture and cultivate learning as a culture. 

To hire the best candidates, they usually rely on employee referrals, careers page, job portals, and social media campaigns. The company is currently hiring analytics consultants and machine learning enthusiasts passionate about Natural Language Processing or Computer Vision. Interested candidates can apply in the careers section of their website.

Growth Opportunities For Data Scientists 

As Preeth shares, Bridgei2i encourages new talent with the right skills and attitude to experiment, learn, and grow. In fact, to begin with, they induct all the employees into the hallway of learning through their Centre of Excellence (CoE) — SCaLa, which features comprehensively-designed courses, and seasoned subject matter experts as instructors. 

“When it comes to providing a good career foundation for our employees, our capability development and skilling platform, SCaLA (Short for Skills, Capabilities, Leadership and Ascension) ensures that employees are given the best learning and growth opportunities in whichever career path they choose,” she said.

Some of the other initiatives by the company are:

  • Learn & Grow (LeGo) initiative that prepares students recruited from campuses to adjust to the professional environment
  • ACCENDO, which is their annual innovation fiesta modelled on a hackathon. It invites participation and collaboration among different teams to create unique solutions, among others. 

“We also have a data-driven, merit-based recognition system that factors both effort and outcomes with a strong focus on contribution to BRIDGEi2i values,” added Preeth. Apart from this, they encourage employees to work in cross-industry and cross-function roles across geographies. “At BRIDGEi2i, we believe in nurturing our talent pool with value-based learning and offer a structured growth path — be it leadership or subject matter experts,” said Preeth on a concluding note.

More Great AIM Stories

Srishti Deoras
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.

More Stories

OUR UPCOMING EVENTS

8th April | In-person Conference | Hotel Radisson Blue, Bangalore

Organized by Analytics India Magazine

View Event >>

30th Apr | Virtual conference

Organized by Analytics India Magazine

View Event >>

MORE FROM AIM
Yugesh Verma
All you need to know about Graph Embeddings

Embeddings can be the subgroups of a group, similarly, in graph theory embedding of a graph can be considered as a representation of a graph on a surface, where points of that surface are made up of vertices and arcs are made up of edges

Yugesh Verma
A beginner’s guide to Spatio-Temporal graph neural networks

Spatio-temporal graphs are made of static structures and time-varying features, and such information in a graph requires a neural network that can deal with time-varying features of the graph. Neural networks which are developed to deal with time-varying features of the graph can be considered as Spatio-temporal graph neural networks. 

Yugesh Verma
A guide to explainable named entity recognition

Named entity recognition (NER) is difficult to understand how the process of NER worked in the background or how the process is behaving with the data, it needs more explainability. we can make it more explainable.

Yugesh Verma
10 real-life applications of Genetic Optimization

Genetic algorithms have a variety of applications, and one of the basic applications of genetic algorithms can be the optimization of problems and solutions. We use optimization for finding the best solution to any problem. Optimization using genetic algorithms can be considered genetic optimization

Yugesh Verma
How to Visualize Backpropagation in Neural Networks?

The backpropagation algorithm computes the gradient of the loss function with respect to the weights. these algorithms are complex and visualizing backpropagation algorithms can help us in understanding its procedure in neural network.

3 Ways to Join our Community

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Telegram Channel

Discover special offers, top stories, upcoming events, and more.

Subscribe to our newsletter

Get the latest updates from AIM