MFine Data Science Hiring Process

MFine is one of the main telemedicine players in the country. As an on-demand digital primary health care platform that provides professional diagnostic and health check-up services, the company partners with thousands of leading hospitals, physicians and diagnostic centers in India to provide high quality primary health care services directly to consumers using artificial care. intelligence (AI) and mobile technology.

MFine’s data science team have been instrumental in everything they do today. “There are many projects that have evolved into high impact products,” said Ajit Narayanan, technical director of I’m fine. For example, he said their core consultation product that millions of his clients use is currently aided by his “virtual doctor,” who coordinates more than 80% of cases. Recently, the company introduced a new function for monitoring SpO2 on mobile using the rear camera. Currently in beta stage, it can save many lives without any investment from users.

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In the past, the team has also provided other solutions, such as the lab report reader, which extracts lab parameters and values ​​from the lab report. It plots users’ lab results longitudinally in the app. “There are many more within the app and ensure smooth viewing on the platform,” Narayanan said.

Team structure

At MFine, the data science team is part of the product and technology team with approximately eight members. The company has subdivided the team based on the types of medical units they receive from their patients on the MFine platform. These are computer vision (for looking at pictures of patients’ problems or pictures of their reports), NLP (conversations between doctor and patient) and machine learning specialists (for reasoning ).

Currently, MFine’s data science team operates on two models: knowledge and discovery. In insights mode, the projects undertaken by the team are mainly based on medical insights derived from the statistical analysis of millions of data points on the MFine platform. These projects not only help improve existing product lines, but also help drive the transformation of products through AI.

In discovery mode, the team interacts directly with physicians and performs comprehensive reviews of clinical literature to develop new, futuristic healthcare solutions. These projects should evolve into trades between 6 months and 2 years, depending on the needs of the market.

In an expansion mode, MFine is now looking to hire senior data scientists with four to seven years of professional experience.

Interview process

“The interview process varies depending on the experience of the candidate we wish to hire,” said Narayan. For example, novice applicants can be expected to demonstrate their practical programming skills. On the other hand, more experienced applicants will have to present their previous work and explain other ways to solve the same problem in the first round.

This would be followed by a deep dive into the technological questions tailored to the real data science problems they solve at MFine. Finally, applicants are assessed on their brainstorming skills, approach to feedback, technical depth, communication skills, and cultural fit.

Expectations

At an entry level, data scientists should be able to:

• Understand and implement cutting-edge AI algorithms
• R&D of AI algorithms
• Develop proofs of concept and produce algorithms

Nikhil Narayan, director of data science at MFine, said senior data scientists should be responsible for understanding and translating clinical needs into a data science problem statement, designing AI solutions , acquire interdisciplinary expertise in the field and interact closely with DevOps and the product. teams. Additionally, he said the candidate should be familiar with upcoming MLOP trends, mentor data scientists, publish patents and papers, manage clinical collaborations, and partner with industry and academia.

MFine assesses data science candidates based on ownership, expertise and impact.

“Candidates are responsible for proposing and appropriating their solutions from design to production and integration into products. Expertise relates to domain knowledge that candidates already have and are learning on the job. Agile learning is one of the traits we look for in candidates during interview and assessment. Impact refers to whether the candidate’s proposed solution directly contributes to a business need or research problem, ”said Narayanan.

Dos and Don’ts

Narayan said there was a lot of emphasis on mindset and behavioral traits at MFine. “We are looking for candidates who are not afraid to fail, are able to learn without inhibitions, can challenge the status quo, are helpful, are open to feedback, have an open mindset and are not working in silos, “he added.

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Additionally, speaking about the common mistake the candidate made when interviewing for data science positions at MFine, Narayan said that many candidates assume that deep learning is the only way to solve a statement. of problem.

Work culture

“Few startups have a fixed model for work culture, but at MFine we have a good, proven model,” said Narayanan. He said their work culture follows an engineering model outlined by the Wharton School at the University of Pennsylvania. The company believes it has created an environment that fosters a performance-oriented and successful candidate who possesses interdisciplinary problem-solving skills.

On top of that, Narayanan, who leads the data science team at MFine, said her team has the freedom to pace their work according to their comfort, as they strongly believe in the mental well-being of members of the team. ‘team. “Healthcare is perhaps the only area where all modalities are used simultaneously to solve a task at hand. So there is a lot of room for multitasking, multimodal research and development on some of the most difficult datasets one can come across, ”said Narayanan.

Additionally, he said problem statements are difficult and are fine for someone after gaining a large amount of knowledge in a very short period of time. “This is probably the biggest advantage of joining a startup where there are no boundaries between teams, and everyone can get involved to solve a common goal,” said Narayanan.

In addition to this, the company also offers other benefits like free medical consultation for employees and family on the MFine platform, free food, flexible working hours, flexible workplaces and a good health insurance, to name a few.

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