Fintech Hiring Trends

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Intoduction

Fintech is the new technology and innovation that aims to compete with traditional financial methods in the delivery of financial services. It is an emerging industry that uses technology to improve activities in finance.The use of smartphones for mobile banking, investing services and cryptocurrency are examples of technologies aiming to make financial services more accessible to the general public.

Goal

In this research we intended to find relevant growth of fintech by analyzing the demands for the fintech jobs needed by largest US banks. We gathered the data of the banks and performed relevant data analysis to get to the conclusion of how and by what margin the fintech industry is growing.

Overview

• Methods : Data mining, Data Scraping, Data Engineering
• Skills : Python programming, Analyzing data, Generate Visualization, Data cleansing, Pipelinig
• Deliverables : Docker image of pipeling, Visualization Report, Analysis report

My role

To lead one of the tewelve teams which was responsible for scraping data of 2 of 24 banks and generating datasets. My teammates (3) were responsible for data gathering, merging from other 11 teams. I was also involved in the phases of data cleansing, feature engineering, data analysis and generating reports.

Process Overview

Research Strategy

1. Building Dictionary

We fetched the text from reports on Fintech by World Economic Forum, based on the fetched text we tokenized each word using bigram, unigram techniques. The tokenized words were then lametized and later ranked using tf-idf vectorizer and wordcount strategy.

Below is the wordcloud of the reports
Word clouds (also known as text clouds or tag clouds) work in a simple way: the more a specific word appears in a source of textual data (such as a speech, blog post, or database), the bigger and bolder it appears in the word cloud.

The ranked top 104 words were then clustered in 9 different buckets based on their relevance.We considered 9 buckets ie Payments, Blockchain, Trading, Investment, Lending,Insurance , Data & Analytics, Security and Software Development. Then we further divided these buckets into two buckets ,Financial and Technology. The words related to the financial domain were classified under the finance domain and the words related to the technical domain were classified under the technology domain.

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2. Fetching Bank Hiring Data

We scraped / mined career webpages of banks and fetched each job posting for past 2 weeks for relevant analysis. The process also involved checking of each job post for the next 3 weeks to deduce that how fast the job posting are being filled by the applicants.

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3. Feature Engineering - Classifying job as fintech or non-fintech

Algorithm followed to decide if a job is Fintech or not and the reason behind it ?

Step 1. Compare the words in the Dictionary with the job descriptions total count of financial and technical words from the job description.

Analysis

Job Openings in USA

As of February 2019, JP Morgan had the largest job opening with estimated count of around 535 followed by Bank Of America (472) and Capital One(314).

Top Location for hiring

Inferring data we observed that NYC has largest job openings, followed by Atlanta and Riverwoods

Overview of Job Buckets

Below bar chart helps us to conclude that the number of pure fintech jobs is slightly greater than the pure technology jobs where as the finance jobs outweigh both by a very large number.

Top Location for hiring

We segregated the data firstly on the basis of the link status that is whether the links are active or not. Then we used the filter of location that is whether a job location is in USA or not. Then we plotted the graph between the axes : the name of the banks and the count of the fintech jobs and non fintech jobs in those banks.We concluded that the number of job openings in both Fintech and non Fintech are the highest in JP Morgan followed by Bank Of America where as Fifth Third bank has the least number of openings in both the sectors.

Overall Comparison

Using both the filters that is whether a link is active or not and that whether the jobs are fintech or not we plotted the overall comparison. We concluded that the weightage of active non fintech jobs is greater than the active fintech jobs by a significant amount and the same conclusion was made that the inactive non fintech job was greater than inactive fintech jobs.

Inferences

As per the analysis, we see that the category with the greatest number of Fintech Job is ine the Technology Development sector. This clears the common misconception that Tech Development or Software Development cannot be a key area of Fintech. Our analysis also shows that most of the banks in U.S are hiring in the Fintech sector for about 20% of their overall job openings in and out of the country. What Fintech strives is to apply technology to ease the delivery of financial services. As we all know, there can be no data without an application, there could only be analytics if there are applications or software to generate that data. So, this justifies our analysis that Tech Development is also a Key area of Fintech Job. The other key areas of Fintech as we categorized are Data & Analytics, Applied Security, Trading, Investments, Payments, Lending and Insurance. So, as we look through these key areas in our analysis for the top 24 banks, we can say that an individual who is looking for a Tech or Analytics in the Fintech Industry will find the most number opportunities within the country as well as offshore.

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M - Sanitation

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Intoduction

Sanitation is an important aspect that needs to be addressed on a very large scale as it affects the public health conditions. One of the major factor that comes into consideration with this is public defecation. It has been observed quite frequently that open defecation leads to many health related problems. Moreover these cases are recorded from the rural areas of India where people are not aware of the consequences of lack of sanitation and hygiene.

Considering these needs, we have come up with a survey which could help to reduce the sanitation crisses faced by India

Goal

This research addresses the snaitation problems faced by people in rural and urban areas and find a relevant solution that can help to reduce the detrimental cost of unhygeinic sanitation condition.

Overview

• Methods : Report Review, Surveys - Online and Onground, ML Model development, Application Development
• Skills : Data Science, Analysis, Interviewing
• Deliverables : Survey paper, Application Prototype

My role

To develop application, conduct online surveys as well as analyze them and maintain a communication bridge between development team and onground survey team in India.

Team Members

Siddhesh Keshkamat, Avinash Chourasiya, Vaibhav Raj, Rohit Jain

Process Overview

Statistics Study

World's Number

We fetched the text from reports on Fintech by World Economic Forum, based on the fetched text we tokenized each word using bigram, unigram techniques. The tokenized words were then lametized and later ranked using tf-idf vectorizer and wordcount strategy.

India's Standing

We fetched the text from reports on Fintech by World Economic Forum, based on the fetched text we tokenized each word using bigram, unigram techniques. The tokenized words were then lametized and later ranked using tf-idf vectorizer and wordcount strategy.

Survey

1. Oneline Survey

Conducted in between the month of July 2018 to August 2018 we had asked users from different cities about different questions related to the sanitatary condition.

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Survey Design
The following consideration was given that participant names would never be asked as talking on the idea of sanitation and having a direct criticism of any authority could lead to unappropriate outcome and also there could be probablity of getting a false answer.
The design process then moved forward with writing down a bit of information related to sanitation to deduce a set of question on the topic. We had also designed specific question related to participant residing in 4 major metropolitan area, rural areas and five different parts which included North, South, West, East, North East.

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The survey report

Step 1. Compare the words in the Dictionary with the job descriptions total count of financial and technical words from the job description.

Analysis

Job Openings in USA

As of February 2019, JP Morgan had the largest job opening with estimated count of around 535 followed by Bank Of America (472) and Capital One(314).

Top Location for hiring

Inferring data we observed that NYC has largest job openings, followed by Atlanta and Riverwoods

Overview of Job Buckets

Below bar chart helps us to conclude that the number of pure fintech jobs is slightly greater than the pure technology jobs where as the finance jobs outweigh both by a very large number.

Top Location for hiring

We segregated the data firstly on the basis of the link status that is whether the links are active or not. Then we used the filter of location that is whether a job location is in USA or not. Then we plotted the graph between the axes : the name of the banks and the count of the fintech jobs and non fintech jobs in those banks.We concluded that the number of job openings in both Fintech and non Fintech are the highest in JP Morgan followed by Bank Of America where as Fifth Third bank has the least number of openings in both the sectors.

Overall Comparison

Using both the filters that is whether a link is active or not and that whether the jobs are fintech or not we plotted the overall comparison. We concluded that the weightage of active non fintech jobs is greater than the active fintech jobs by a significant amount and the same conclusion was made that the inactive non fintech job was greater than inactive fintech jobs.

Inferences

As per the analysis, we see that the category with the greatest number of Fintech Job is ine the Technology Development sector. This clears the common misconception that Tech Development or Software Development cannot be a key area of Fintech. Our analysis also shows that most of the banks in U.S are hiring in the Fintech sector for about 20% of their overall job openings in and out of the country. What Fintech strives is to apply technology to ease the delivery of financial services. As we all know, there can be no data without an application, there could only be analytics if there are applications or software to generate that data. So, this justifies our analysis that Tech Development is also a Key area of Fintech Job. The other key areas of Fintech as we categorized are Data & Analytics, Applied Security, Trading, Investments, Payments, Lending and Insurance. So, as we look through these key areas in our analysis for the top 24 banks, we can say that an individual who is looking for a Tech or Analytics in the Fintech Industry will find the most number opportunities within the country as well as offshore.

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