Edward Flores's Avatar
Edward Flores
published in Blogs
Feb 10, 2021
Can Data Scientists Profit from the Market...Without Trading?

Can Data Scientists Profit from the Market...Without Trading?

Before I dive into how to become a data scientist, let me first establish a few basic facts. The first of which is, what does a data scientist even do? The simplest definition is that a Data Scientist engages in the practice of collecting, analyzing, and interpreting data – aided by technology. That last bit is key, because advances in technology – particularly AI – are fundamentally changing how data scientists and statisticians process and analyze data.

So, where do data scientists work? And how can you make money as a data scientist?

One thing is for sure – data scientists are in high demand, and that demand looks only set to grow from here. As it stands today, data scientists are primarily found in the tech industry or in companies with a well-developed IT component, since those are generally the types of companies that collect, store, and analyze huge volumes of data. Traditional companies have not quite caught up in the world of large-scale data analysis, but most companies that want to survive in the 21st century know that they need to do so fast. Data is king.

There is another way people can make money as data scientists – using data analysis to invent your own ideas, strategies, and insights. And then selling those ideas. This actually happens more often than you might think. Many initial coin offerings (ICOs) in the cryptocurrency world are issued by teams of developers, computer scientists, and data scientists who have invented a new process, protocol, or strategy for performing a function better and more efficiently.

 

 

In the world of finance, Tickeron offers a platform for data scientists to sell their ideas, in a marketplace called MALL. Imagine a situation where a data scientist creates an algorithm that generates trade ideas based on analysis of say, a massive data set of corporate earnings. The data scientist then keeps statistics on the performance of their algorithm, and finds that it is successful 60% of the time. That is an idea worth selling! In Tickeron’s MALL, a data scientist can do just that.  

What Do I Need to Learn to Become a Data Scientist?

Interestingly, the profession of Data Scientist is so new that many Computer Science degrees at major universities do not yet offer Data Science as a major. As such, many Data Scientists are self-taught and it is possible to become a Data Scientist without a formal degree.

First off, if statistics isn’t something you’re interested in, maybe Data Scientist isn’t a great career choice for you. While being a Data Scientist and a Statistician are not the same thing, a strong understanding of statistics is probably the most important skillset for Data Scientists. To put it simply, all of the programming, mathematical, and software skills in the world will not help you if you don't understand how to analyze and report on statistics accurately and fairly. If you don't understand the theory behind confidence intervals, appropriate sample size, and statistical significance, you are not likely to make accurate assessments and claims.

If you enjoy statistics and have a deep interest in understanding all of its nuances, then from there you’ll want to deep-dive into each of the following subjects:

·      Linear algebra, including multivariate calculus

·      Regression, including the ability to handle both linear and nonlinear models

·      Probability theory, including Bayes' Law and Central Limit Theorem

·      Numerical analysis, including time series analysis and forecasting

·      Core machine learning methods, including clustering, decision trees, and k-NN

·      Programming, with an emphasis on writing scripts to automate the process of cleaning and preparing data for analysis. Python is a dominant language in the programming field, followed by the R programming language.

The best part is, most of these functions can be learned online through free or low-cost courses. You just have to be willing and committed to put in the time.

 

 

What are Some of the Day-to-Day Functions of a Data Scientist?

Data scientists can work in a variety of fields, and can have functions that range from simulating the spread of an epidemic, to analyzing stock charts for a hedge fund in search of technical trading patterns, to using data, models, and analytics to more effectively market a product on the web or social media. Anywhere that data is collected, it can be used to more effectively carry out a process – period.

As I mentioned before, the role of Data Scientist is becoming more and more prevalent in the world today, as data is recognized as the most effective tool needed to run a business more efficiently. Data scientists are the ones who take the data, analyze it, and interpret it so the company can get better and do better. They’re fundamentally changing the way businesses operate.

In the world of finance, given the near endless amount of data available in the capital markets, data scientists have the ability to invent new trading techniques and strategies that can change the way people invest. And Tickeron wants to give these innovative data scientists the opportunity to share their discoveries and ideas to the world.

Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Mar 07, 2021
4 Tricks Hedge Funds Use to Get Ahead

4 Tricks Hedge Funds Use to Get Ahead

If the stock market were Major League Baseball, hedge funds and institutional investors would be the pros on championship teams while everyday self-directed investors (SDIs) are the benchwarmers in the minors.It’s how they get ahead, and it’s why 90% of SDIs lose money trying to play (invest and trade) in the major leagues. The 4 tricks we discuss below are rooted in one common theme: they all use Artificial Intelligence and algorithms to generate data and ideas.
John Jacques's Avatar
John Jacques
published in Blogs
Mar 22, 2018
A.I. Stock Market Predictions: Head & Shoulders

A.I. Stock Market Predictions: Head & Shoulders

Statistics for the Head-and-Shoulders Bottom Pattern The days where only hedge funds used algorithms to trade stocks are officially over. Now retail investors can use Artificial Intelligence (A.I.  Here’s an example of the algorithm in action: Late last year, Tickeron’s A.I.
Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Jul 10, 2020
3 Stocks to Buy if Coronavirus Second Wave Hits

3 Stocks to Buy if Coronavirus Second Wave Hits

By analyzing market trends from the first wave, you can predict behavior for the second. Technology stocks have performed at historic levels this year, but the market is severely overbought.To compensate for that, look at performance during Q1 and Q2, the height of global Covid shutdowns.
Edward Flores's Avatar
Edward Flores
published in Blogs
Feb 06, 2021
How to Become the Millionaire Next Door

How to Become the Millionaire Next Door

The Golden Gate Bridge is always a fixture of these walks too, one of man's most beautiful creations.  As we were walking, at one point she turned to me and said, "Man, I'll never have a million dollars."" My girlfriend is 27 years old and works as a graphic designer, making about $75,000 a year.
Alla Petriaieva's Avatar
Alla Petriaieva
published in Blogs
Feb 23, 2021
Is Ethereum’s Bomb about to Explode?

Is Ethereum’s Bomb about to Explode?

Ethereum’s software is set for an update in October.Until it is finished, participants in the Ethereum blockchain must determine how to delay the difficulty bomb – code that necessitates a steadily increasing amount of computer power to mine blocks and unlock rewards – that is already in place.
Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Aug 07, 2018
When Is the Next Recession Coming?

When Is the Next Recession Coming?

However, we also know that economists predicted 22 recessions out of 11 that took place since 1945. Are there real recession signs we should watch for?Indeed, the answer is yes, and here are a few very important ones: The first one is almost obvious and known to everyone – it is the Fed.
Abhoy Sarkar's Avatar
Abhoy Sarkar
published in Blogs
May 22, 2020
Central banks have been buying $2.4 billion in assets every hour for the past two months

Central banks have been buying $2.4 billion in assets every hour for the past two months

Some $17.8 billion has been poured into  bond markets over the past week, the biggest move in more than three months.Around $3.5 billion has been invested into gold, the second largest on record. 
Rick Pendergraft's Avatar
Rick Pendergraft
published in Blogs
Feb 07, 2021
Mid-January Short Interest Report Shows 8 Stocks with Good Fundamentals and High Short Interest
Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Mar 10, 2021
How to Start Trading Penny Stocks

How to Start Trading Penny Stocks

Penny stocks have long been marginalized within the professional investment community, oftentimes being painted with a broad brush of simply being “too risky.” Leonardo DiCaprio’s depiction of the penny stock peddling conman, Jordan Belfort, in the Wolf of Wall Street certainly didn’t help.Here are four reasons to start trading them now. Reason #1: Let’s State the Obvious -- Penny Stocks are Cheap A single share of Apple Inc. costs over $350.
Abhoy Sarkar's Avatar
Abhoy Sarkar
published in Blogs
May 08, 2020
US unemployment rate jumps to 14.7%, the highest in series history

US unemployment rate jumps to 14.7%, the highest in series history

The U.S. economy’s employment fell by -20.5 million in April. The coronavirus crisis led to unemployment rate soaring to 14.7% in the U.S, the highest rate in the Bureau of Labor Statistics-tracked series history that goes back to 1948. However, the figures were better compared to several economists'/analysts' forecasts of 22 million job losses and 16% unemployment rate.  Another unemployment measure that includes those who have stopped looking for work as well as those holding part-time jobs for economic reasons also touched an all-time high of 22.8%.