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Data science is used to identify future users of other apps and to determine who is more likely to purchase premium subscriptions. "Data science models are used to prioritize all cross-selling and lead conversion activities," Naresh explained.

Furthermore, he stated that at our Company, risk is managed by a combination of auto-blockers that prohibit suspicious users based on pre-set restrictions and a Machine Learning model that assigns a risk score to possible fraud users.

"Within the our Company payment ecosystem, the auto-blockers and ML-based risk model operate in unison to avoid fraud." "Our CTS (check truncation system) and FTS (fraud to sales) rates have stayed strong and well below industry cutoffs," Naresh explained.

ON (Expanding Mode)

The company is now looking for different data science positions, including director of data science, associate director of  manager analytics, and senior data scientist, according to Analytics India Magazine. Candidates with three to eight years of experience are being sought by the organization.

Our Company is looking for data scientists and Machine Learning experts to help them achieve three major goals.

>>Determining the legitimacy of merchants for the sake of fraud risk and lending

>>Forecasting business performance and making appropriate plans 

>>To save time and effort, personalize the product and build AI products.

Structure of the Group

The analytics and data science team of katabook has 30 members.

our Company has a centralized analytics and data science role. our Company, for example, has five products, each with a data science head and a team of 4-5 data analysts and scientists.

Process of Interviewing

our Company data science function is divided into two parts: business analytics and Machine Learning

As a result, the business analytics interview process would contain

1.Knockout round (technical analysis + business case study) after the screening round

2.Another round of technical analysis

3.Round of analytics case studies

4.round of business heads

5.Round of cultural compatibility

The interview process for Machine Learning would involve the following:

6.Knockout round (previous projects + machine learning principles)

7.Machine learning round of technical analysis

8 Round of business case studies

9 .ML technological project (hands-on coding)

10 .Round of cultural compatibility

Skills

 

Working at our Company necessitates a variety of abilities.

1 .Technical skills: SQL, Excel, and other scripting languages are a plus (Python, R, etc.)

2 .Extensive experience with business intelligence tools (Tableau, Power BI, etc.)

Tools for Data Science

3 .Git, Airflow, Tensor flow, Keras, MLO ps, Mix panel, Snowflake, Tableau, and other tools are used by our Company.

Expectations

The ideal applicant, according to our Company, should be able to exhibit four fundamental abilities:

1 Good business sense and systematic problem-solving abilities are required.

2 Product knowledge that is second to none

3 Expertise in machine learning/analytics approaches is required.

4 a strong sense of belonging

Aside from these, some of the additional Criteria

Understanding the business uses of machine learning and analytics

A solid background in statistics or machine learning algorithms that are applicable to roles

Focus on business value created from insights; bias towards action

Writing production-ready code that is clean and optimised When it comes to our Company, what can you expect? 

Don'ts and Do

Most candidates who apply for data science jobs at our Company, according to Naresh, prioritise describing the models over comprehending the problem. Furthermore, he claims that they do not place a high value on presenting abilities and are less clear while discussing the assignment.

When it comes to our Company, what can you expect?

our Company works in the field of developing market technology. Many of the users have never used the internet before. More fresh data is being generated as a result of the rise in digital adoption, offering a tremendous opportunity for the team to engage on innovative use cases and problem-solving. In addition, consumer behavior in emerging markets is rapidly changing. This makes our Company a fascinating location to work for any data scientist.

In addition, our Company provides a slew of employee benefits, including unlimited vacation time, extended paternity leave, weekly company-wide mental health breaks at regular intervals, no meetings Wednesdays, referral bonuses, internet and home office expense claims, virtual team feasts, vaccine drives for employees, and virtual team cultural events, all of which contribute to a strong work culture and collaborative team environment.

Are you all set?

Finally, here are some essential considerations while applying for data science positions at our Company

Prepare an answer to the question about your work's commercial value.

Brush up on the fundamentals underpinning the machine learning techniques you're already familiar with, as well as their broader commercial implications.

Learn how to solve case studies and work with unstructured challenges.

To apply models in production, you should have a thorough understanding of data engineering fundamentals.

Get......your Future with our Company