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PRIYANKA NAYAK S liked Jeffrey Ng's blog post Works of business analyst BA explained
May 12
Jeffrey Ng's blog post was featured

What do I learn from developing Analytics in a weird place?

4 years ago, before all these hype on Big Data Analytics, right after my MBA, I dream about the digital future in investment banking. I visualized it in my mind, based on what I learnt in retail banking, and credit risk modeling, I feel that it was a possible dream. A dream that was so fragile that it could be popped one day. Or it could be a super-long journey that leads me via fire and pain or even be embarrassed. Looking back, these are the lessons I learnt:1. Intra-preneur: It is pretty…See More
Feb 11, 2016
Jeffrey Ng updated their profile
Feb 9, 2016
Jeffrey Ng commented on Jenny Richards's blog post Comparing MongoDB with MySQL
"good stuff! is MongoDB the best NoSQL product? how about the connectivity from R / Python? Which is easier and popular?"
Jun 27, 2015
Jeffrey Ng posted a blog post

R or Python, a practical problem

Which technology works best in a team when we are introducing data mining. The team has been using Excel as the data analysis tool, how can we apply/ run the data mining model (such as decision tree) on excel? I have been using R for a while and enjoy it very much. Good supply of fresh grad with training in R...However, when it comes to using and running the data mining model, R does a very poor job in execution. It is such a good tool when we develop and research patterns in a laboratory where…See More
Jun 17, 2015
Jeffrey Ng's blog post was featured

How Analytics help in Corporate & Institutional Banking?

There is a fire, everything burnt into ashes, reborn the phoenix.Challenges faced by the industryIt happens to every industry, the down cycle is the time to restructure, optimize for the longer journey. The same happening to the investment banking industry. Weighted by public scrutiny and heavier regulation on disclosure, rounds of cost cutting and restructuring follows. Silicon Valley has overtaken Wall Street as the destination of the brightest. Would it be more attractive if we can do a…See More
May 27, 2015
Shankar S commented on Jeffrey Ng's blog post Why bother building a model while you have a good human doing the work?
"Greetings, Nice article and discussion. Just want to add a point to the side favoring models over human expertise: its laying the infrastructure for fine-tuning the model(s) to suit other scenarios/related problems etc. Once the basic process is…"
Apr 30, 2015
Jeffrey Ng commented on Jeffrey Ng's blog post Why bother building a model while you have a good human doing the work?
"can you look for a smaller problem to build up your credential? Your problem seems to be two-folded - you lack the credential internally; and secondly, the management lacks the quality to respect the model. this is two-sided. think in their shoes…"
Apr 8, 2015
Thomas Lincoln commented on Jeffrey Ng's blog post Why bother building a model while you have a good human doing the work?
"Jeffery, I have done all the operational data collection for my division.  I did it better than the IT department in their data warehouse.  I understand the operational issues having an operational undergraduate degree and having…"
Apr 8, 2015
Jeffrey Ng commented on Jeffrey Ng's blog post Why bother building a model while you have a good human doing the work?
"I can share what you can do, if you truly believe in the values of models: 1. Build it yourself and evwn if u can get it off the shelf. This will help you to collect what data is important to the models. 2. Collect, store and report data on…"
Apr 8, 2015
Thomas Lincoln commented on Jeffrey Ng's blog post Why bother building a model while you have a good human doing the work?
"Actually, its more of a human behavioral issue that models can't be manipulated like people, therefore a robotic model is more risky, and less trustworthy to give the executive what he wants to hear, versus what he wants to know. .…"
Apr 6, 2015
Jeffrey Ng commented on Jeffrey Ng's blog post Why bother building a model while you have a good human doing the work?
"My experience told me that u need to find the less senior one but denior enough to believe in data and model. I waited 2 years before I got my first internal client, then it will spread like wild fire."
Apr 6, 2015
Jeffrey Ng commented on Jeffrey Ng's blog post Predictive Analytics: When to use or not to use a consultant?
"Hi Ammanuel, I have further thought about it, perhaps it may help: https://hbr.org/2010/08/how-to-sell-an-idea-to-your-bo"
Jan 13, 2015
Jeffrey Ng commented on Jeffrey Ng's blog post Predictive Analytics: When to use or not to use a consultant?
"For internal lobbying - can try to find some existing works that can be enhanced by predictive Analytics - less time, less human intervention. It can be a project that no one want to do it but can be easier delivered if using machine; or a work that…"
Jan 6, 2015
Emmanuel commented on Jeffrey Ng's blog post Predictive Analytics: When to use or not to use a consultant?
"I believe I am stuck somewhere in between  starting and learning. I have kick started the personal journey into Predictive Analytics and I am less than a year into that journey but still no major project in my bag. I can appreciate the…"
Jan 4, 2015
Jeffrey Ng's blog post was featured

Predictive Analytics: When to use or not to use a consultant?

There are two circumstances that you should use a consultant:1. When the consultant has both the domain knowledge and exact modeling experience: There are times that the consultant come to you and sell you the ideas of modeling something. Look for exact experience. Like an academic researchers, the most challenging task is to get the data-set, not the idea. Dataset is the execution. In the world of Big Data analytics - whoever owns the data has the command, especially in the commerical world.…See More
Dec 26, 2014

Profile Information

Short Bio:
Customer Analytic in the investment banking industry in APAC
My Website or LinkedIn Profile (URL):
http://www.linkedin.com/pub/jeffrey-hm-ng/21/744/8b2
Field of Expertise:
Business Analytics, Predictive Modeling, Data Mining, Marketing Databases, Operations Research, Econometrics, Statistical Programming, Statistical Consulting, Artificial Intelligence
Years of Experience in Analytical Role:
10
Professional Status:
VP, Consultant
Interests:
Finding a New Position, Networking
Your Company:
International Bank
Industry:
Banking: Retail, Corporate & Investment banking
Your Job Title:
Head of Department
How did you find out about AnalyticBridge?
Linkedln

Jeffrey Ng's Blog

What do I learn from developing Analytics in a weird place?

Posted on February 9, 2016 at 8:58am 0 Comments

4 years ago, before all these hype on Big Data Analytics, right after my MBA, I dream about the digital future in investment banking. I visualized it in my mind, based on what I learnt in retail banking, and credit risk modeling, I feel that it was a possible dream. A dream that was so fragile that it could be popped one day. Or it could be a super-long journey that leads me via fire and pain or even be embarrassed. Looking back, these are the lessons I learnt:

1. Intra-preneur: It is…

Continue

R or Python, a practical problem

Posted on June 16, 2015 at 11:14am 0 Comments

Which technology works best in a team when we are introducing data mining. The team has been using Excel as the data analysis tool, how can we apply/ run the data mining model (such as decision tree) on excel? I have been using R for a while and enjoy it very much. Good supply of fresh grad with training in R...However, when it comes to using and running the data mining model, R does a very poor job in execution. It is such a good tool when we develop and research patterns in a laboratory…

Continue

How Analytics help in Corporate & Institutional Banking?

Posted on May 23, 2015 at 3:30am 0 Comments

There is a fire, everything burnt into ashes, reborn the phoenix.

Challenges faced by the industry

It happens to every industry, the down cycle is the time to restructure, optimize for the longer journey. The same happening to the investment banking industry. Weighted by public scrutiny and heavier regulation on disclosure, rounds of cost cutting and restructuring follows. Silicon Valley has overtaken Wall Street as the…

Continue

Predictive Analytics: When to use or not to use a consultant?

Posted on December 26, 2014 at 3:00am 3 Comments

There are two circumstances that you should use a consultant:

1. When the consultant has both the domain knowledge and exact modeling experience: There are times that the consultant come to you and sell you the ideas of modeling something. Look for exact experience. Like an academic researchers, the most challenging task is to get the data-set, not the idea. Dataset is the execution. In the world of Big Data analytics - whoever owns the data has the command, especially in the…

Continue

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