What NYC industries are hiring data analytics-trained employees?
Data-related careers have been on the rise for several years and the trends show no meaningful signs of slowing down. Per the Bureau of Labor Statistics, data science jobs are anticipated to grow 36% over the next decade, which is nearly ten times faster than the national average of 4% growth. These in-demand jobs are also high paying careers, earning an average salary of over $100,000 annually. In NYC, salaries will be even higher and there are numerous different industries hiring data experts for a variety of different roles.
NYC is the home of some of the largest financial institutions and markets in the world, so much so that Wall Street has come to define the culture of the city. NYC is home to some of the giants of the finance and banking industry, counting firms like JP Morgan Chase, Morgan Stanley and Goldman Sachs among their ranks. Unsurprisingly, a city that produces this much financial activity produces an equally large amount of financial data, and it is up to data professionals to parse and interpret this data for their employers and clients. This requires them to understand the logical practices of data analytics and it places demand on them to understand the technological side of data analytics. Since so much data is generated every day, it is moving significantly faster than a human being can keep up with. Top-tier professionals will need to understand how to use tools like machine learning algorithms and AI tools in order to keep a competitive edge over the competition. This demand for data skills across multiple industries highlights why learning data analytics is more important than ever.
New York City is also one of the commerce hubs of the world, and while its reputation as the Mecca of shopping has waned, retail and fashion remain important parts of the consumer economy. Famous storefronts like Macy’s, Nordstrom, Bloomingdales, and Saks 5th Avenue remain pillars of the NYC retail market. These companies will all rely on data analytics experts to keep records of customer behavior and spending habits in order to make informed decisions concerning the best approach to everything from advertising to product offerings. These experts are tasked with using data to predict consumer behavior, which tends to be significantly more data-driven as we become more and more adept at tracking individuals with statistical metrics (for example, we can now generally tell how long individual customers are spending in a digital storefront). This kind of data analysis is vital to the long-term health of a business and thus, businesses of all stripes are interested in securing top-tier talent from their analysts.
With a population of over 8 million permanent residents and a commuter base pushing that number well over 10 million on any given day, the five boroughs and adjacent suburbs would be the 12th largest state in the country by population. This means that NYC requires its own massive government in order to operate everything from public services to the subway to its Department of Education. These projects all require data specialists who can track public opinion, develop optimal strategies for completing projects, and determine whether or not a given project will achieve its goals based on current data metrics.
Finally, if it is the kind of thing that interests you, NYC is home to dozens of sports franchises (from major players like the Yankees and the Liberty to smaller teams like the Jackals, Cyclones, and Staten Island Yankees) and among the largest recreational fitness industries in the nation. Over time, these fields have become increasingly data-driven, with sports teams paying good money for professional analysts who can help eke out small competitive edges with solid data analytics skills. Likewise, fitness professionals are using more and more data-driven methods to help their clientele live healthier lives. Given that you can now easily buy a watch that both checks your email and measures your REM sleep cycle, this amount of data is invaluable for anyone looking to work in fitness (or set their own fitness goals while also working in another unrelated data field).
Will I need to learn to code to succeed in data analytics?
While you don’t have to learn how to code in order to succeed in the field of data analytics, you are definitely leaving a lot on the table by choosing a path that doesn’t involve learning to code. Working with just tools like Excel and Tableau can be very productive, but without learning how to work with programming languages like SQL and Python, you are largely at the mercy of the limitations that other tools have when it comes to working with your databases. For example, while Excel is a very robust program, it is still lacking in terms of querying potential relative to applications and algorithms written using SQL. Likewise, there are a lot of excellent, coding-free ways to collect and clean your data, but none of them are nearly as effective as writing your own application in Python since that program will be built specifically with your work in mind.
By and large, if you are hoping to work in data analytics, particularly in a high-paying industry like FinTech, it pays to know how to write code that can assist you in the specific elements of your projects. With just a few additional programming lessons, you can massively increase your potential as a data analyst and you can start building your own programs to streamline the entire process. This means that if you are looking to learn data analytics in a very competitive market, like the one found in NYC, you will probably want to learn how to code if you want to give yourself the best chance to succeed. If you're preparing for a career change or just looking to break into the industry, it’s worth learning more about how to become a Data Analyst.
What practical things should I consider when learning data analytics?
Data analytics classes tend to be fairly in-depth career-training programs and, as such, will often cost a few thousand dollars and run for several weeks, either as full-time courses or as part-time courses. This means that learning data analytics is going to be a time and financial investment, but as a career-focused training course, you are likely going to receive a lot of benefits and support options as part of your enrollment. These courses are significantly cheaper and faster than comparable college training programs, and they are in-depth enough that you can feel confident in your skills by the time you graduate, making them ideal for anyone looking to start a new career or upskill their existing toolkit.
New York City’s higher cost of living and, on average, higher salaries will tend to make the classes that are offered slightly more expensive than the national average, but not by so much that it is particularly noticeable. In addition, the higher cost of living and higher salaries will mean that the starting salaries for data analytics professionals will be higher, making these professional training programs even more enticing for aspiring career changers.
Learning in-person also means you’ll have to factor in travel time and the cost of a commute when deciding whether or not a data analytics course is worth the time investment. Given the expansive public transportation options available in NYC, you shouldn’t find it difficult to commute to and from class, but it is still something that you’ll need to consider when enrolling in a course.
Cost and financing options
Enrolling in a professional data analytics course will have an up-front cost that you need to consider. Tuition in these courses will often be a few thousand dollars or more, which can seem like a large investment. However, most training programs offer some options for financing your training, paying in installments or receiving credit loans to pay for the tuition. These financing options will differ from program to program, so be sure to check with the various service providers you are looking into to see who’s financing options make the most sense for your situation.
