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Manoj N.

@manojnain24

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Data Scientist

$15 USD / Hour
・
Flag of
India (3:03 AM)
・
Joined on April 12, 2020
$15 USD / Hour
・
Experienced Data Scientist with a demonstrated history of working in the information technology and services industry. Skilled in Big Data Analytics, Machine Learning, Marketing Analytics, Quantitative Research, Big Data. Strong engineering professional with a Master of Business Administration - MBA focused in Business Analytics from Institute of Management and Technology, Delhi, India.
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Freelancer Python Developers India
See all Python Developers in India

Portfolio

Portfolio

6392111
Mobile money transactions are emerging rapidly in the era of Intelligent Machines, while on the flip side fraudulent transactions are on the rise as well. Even with the updated security measures, we are still facing an issue of very high amount of money loss. Let's say a company named as IPAYU has been providing it's financial services to the variety of users in a country. But at the same time there are loopholes in security measures (in the meanwhile company is upgrading it's security). Fraudster might try to crack inside the company's interface and can commit fraudulent transactions. It may harm people trust towards the company. To tackle this situation of crisis, they have consulted a team of data scientists. Now the question is how this problem could be solved using data science?
Fraudulent Transaction Analysis Using Machine Learning
Fraudulent Transaction Analysis Using Machine Learning
Mobile money transactions are emerging rapidly in the era of Intelligent Machines, while on the flip side fraudulent transactions are on the rise as well. Even with the updated security measures, we are still facing an issue of very high amount of money loss. Let's say a company named as IPAYU has been providing it's financial services to the variety of users in a country. But at the same time there are loopholes in security measures (in the meanwhile company is upgrading it's security). Fraudster might try to crack inside the company's interface and can commit fraudulent transactions. It may harm people trust towards the company. To tackle this situation of crisis, they have consulted a team of data scientists. Now the question is how this problem could be solved using data science?
Fraudulent Transaction Analysis Using Machine Learning
6434426
Sales Prediction for a Retail store
Predicting sales of different products across different stores of a retail chain using Regression methods likes Linear Regression, Decision Tree Regressor, Random Forest Regressor.
Sales Prediction for a Retail store
6392104
Credit Default Risk Analysis and Detection
The process of issuing loans has increased in complexity over the years due to the different possibilities, market demands and clients’ circumstances. Many people struggle to get loans due to insufficient or non-existent credit histories. And, unfortunately, this population is often taken advantage of by treacherous lenders. This has made banks a highly regulated entity which is expected to act responsively while providing loans. IndNatBank is a peer to peer loan financial company who provides loan to its potential customers all over the India. Based on the previous data they want to analyze the risk of issuing loans to the new customers which at the same time also helps to improve the personalization user experience while applying for loans. They wants to automate their process by which machine learns the pattern out of their data for better customer experience. Now the question is how this problem could be solved using Machine Learning?
Credit Default Risk Analysis and Detection
6392111
Mobile money transactions are emerging rapidly in the era of Intelligent Machines, while on the flip side fraudulent transactions are on the rise as well. Even with the updated security measures, we are still facing an issue of very high amount of money loss. Let's say a company named as IPAYU has been providing it's financial services to the variety of users in a country. But at the same time there are loopholes in security measures (in the meanwhile company is upgrading it's security). Fraudster might try to crack inside the company's interface and can commit fraudulent transactions. It may harm people trust towards the company. To tackle this situation of crisis, they have consulted a team of data scientists. Now the question is how this problem could be solved using data science?
Fraudulent Transaction Analysis Using Machine Learning
Fraudulent Transaction Analysis Using Machine Learning
Mobile money transactions are emerging rapidly in the era of Intelligent Machines, while on the flip side fraudulent transactions are on the rise as well. Even with the updated security measures, we are still facing an issue of very high amount of money loss. Let's say a company named as IPAYU has been providing it's financial services to the variety of users in a country. But at the same time there are loopholes in security measures (in the meanwhile company is upgrading it's security). Fraudster might try to crack inside the company's interface and can commit fraudulent transactions. It may harm people trust towards the company. To tackle this situation of crisis, they have consulted a team of data scientists. Now the question is how this problem could be solved using data science?
Fraudulent Transaction Analysis Using Machine Learning
6434426
Sales Prediction for a Retail store
Predicting sales of different products across different stores of a retail chain using Regression methods likes Linear Regression, Decision Tree Regressor, Random Forest Regressor.
Sales Prediction for a Retail store
6392104
Credit Default Risk Analysis and Detection
The process of issuing loans has increased in complexity over the years due to the different possibilities, market demands and clients’ circumstances. Many people struggle to get loans due to insufficient or non-existent credit histories. And, unfortunately, this population is often taken advantage of by treacherous lenders. This has made banks a highly regulated entity which is expected to act responsively while providing loans. IndNatBank is a peer to peer loan financial company who provides loan to its potential customers all over the India. Based on the previous data they want to analyze the risk of issuing loans to the new customers which at the same time also helps to improve the personalization user experience while applying for loans. They wants to automate their process by which machine learns the pattern out of their data for better customer experience. Now the question is how this problem could be solved using Machine Learning?
Credit Default Risk Analysis and Detection
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Experience
Data Scientist
Oct, 2019 - Present
•
5 years, 2 months
Living Media
Oct, 2019 - Present
•
5 years, 2 months
• Worked as Analytics Intern from Oct 2019 to April 2020 • Developed a model to understand the sensitivity of subscription price increases on newspaper subscribers. The model suggested the appropriate price increase amount for each customer • Performed a sentiment analysis on the company’s Facebook page to gauge its’ public perception and develop social media strategies for the marketing team to improve social media presence and optimize paid promotions
Oct, 2019 - Present
•
5 years, 2 months
Graduate Teaching Assistent
Sep, 2018 - Mar, 2019
•
6 months, 1 day
IMT, Delhi
Sep, 2018 - Mar, 2019
•
6 months, 1 day
• Conduct lab sessions as Teaching Assistant in Business Statistics, covering topics like probability, regression & visualization
Sep, 2018 - Mar, 2019
•
6 months, 1 day
Decision Scientist
Aug, 2016 - May, 2018
•
1 year, 9 months
MU Sigma
Aug, 2016 - May, 2018
•
1 year, 9 months
• Provided actionable insights to European advertisers on Microsoft Bing Ads platform • Took initiative to mentor multiple batches of new employees and gave lectures on Search Engine Marketing • Won the Spot Award for ownership of end-to-end delivery for mid-market • Created a highly successful product trends report which was made available to all retail advertisers to tailor their bids, targeting the top trending products of a season
Aug, 2016 - May, 2018
•
1 year, 9 months
Education
MBA Business Analytics
2018 - 2020
•
2 years
Flag of
India
2018 - 2020
•
2 years
B.Tech
2012 - 2016
•
4 years
Flag of
India
2012 - 2016
•
4 years
Qualifications
Data Scientist in Python
2019
Dataquest
Python, Data Science, Machine learning, deep learning, SQL, Statistics
2019
Global Certificate in Data Science and Artificial Intelligence
2019
INSAID
Python, Data Science, Machine Learning, Deep Learning, Tableau, Power BI, SQL, Hadoop, Apache Spark
2019
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