Introduction
“Data Scientist: The Sexiest Job of the 21st Century ”is one of the most popular articles in Harvard Business Review (HBR) and has inspired tons of people to follow their careers in the field of analyticsAnalytics refers to the process of collecting, Measure and analyze data to gain valuable insights that facilitate decision-making. In various fields, like business, Health and sport, Analytics Can Identify Patterns and Trends, Optimize processes and improve results. The use of advanced tools and statistical techniques is essential to transform data into applicable and strategic knowledge..... One of the main topics of this article published in HBR was the trend of increasing jobs in the analytics industry.
IBM recently predicted the same inference by saying that the number of EE data professionals. UU. Will increase from 364.000 a 2,72 million for 2020.
And that has happened this year.
Unanimously, across the industry, we are seeing an increase in Business analysis job vacancies, But do all of these jobs need the exact same skill set?? I have received a series of inquiries focused on what are the possible career paths in the analytics industry. These inquiries usually come from people looking for a break in the analytics domain or people already working in the industry and looking for a deeper role..
In this article, we will see the main roles available in the analytics industry. I will also propose a framework to think about your career in the business analytics space.
If you are looking to pursue a career in business analysis, be sure to check out the comprehensive multiple course Certified Business Analysis Program.
Table of Contents
- About the analytics market
- What does a business analytics professional do?
- Report roles
- Intermediate analytical roles
- Strategy roles
- Roles of data scientists
About the analytics market
Let me start with a few lines / data points that were published in a McKinsey report on Big Data (May of 2011):
Only the United States faces a shortage of 140.000 a 190.000 people with analytical experience and 1,5 millions of managers and analysts with the skills to understand and make decisions based on big data analytics.
Pay attention to the words "with the skills to understand and make decisions based on big data analysis". The industry will require a large number of big data and machine learning experts and needs even more (about 10 times) people who can make decisions based on the analysis, even if they are not experts in big data or machine learning.
These roles will be primarily strategy roles and product management roles that can define new challenges for your analytics specialists to solve.. We will contrast these strategic roles with the roles of data scientists later in this article.. First, let's try to understand how diverse this industry really is.
If you draw a word cloud of all articles related to analytics (an example shown in the picture below), you will see all kinds of words appear, including statistics, computer programming, strategy, planning, reports, etc. The field of business analytics is extremely diverse and people with analytical skills and business acumen are sought after across all industries in numerous and diverse roles.. Thinking about your career with so many possible options can be overwhelming and you may feel like you are losing track of whether or not you are progressing in your career..
What does a business analytics professional do?
The word “Business analysis” perfectly sums up each type of work we classify in business analysis. "Business" emphasizes the importance of business understanding, and "Analysis" refers to the importance of statistics, computer engineering and operations research in this type of function.
An analytics professional can, as a last resort, work in a role very focused on strategy or can work as a scientist of deep learningDeep learning, A subdiscipline of artificial intelligence, relies on artificial neural networks to analyze and process large volumes of data. This technique allows machines to learn patterns and perform complex tasks, such as speech recognition and computer vision. Its ability to continuously improve as more data is provided to it makes it a key tool in various industries, from health... very specialized. The first role has a stronger business component, while the second role has a much stronger component of analysis. Obviously, your role usually has a trade-off between these two components and you can switch between roles that have different proportions of the two components. The value you create for yourself is a positively correlated function of business insight and analysis. Mathematically speaking:
Value = function (Business understanding , Analytics)
With this knowledge, I have plotted various roles in our industry in a crosstab chart below:
Obviously, the chart above is my personal understanding of the industry and the position of each function in this chart can certainly be debated. The main idea I want you to focus on is the diversity of roles you can take on in the business analytics industry and the variation in the path you can take from your current role.. Let's first try to understand each of the 5 Boxes highlighted above regarding role category.
Report roles
Between 2000 Y 2012, this was the top category of roles for business analytics professionals. The role referred mainly to “What (event) It happened ”instead of“ Why it happened (the event)”. But nevertheless, Most of these roles have evolved in recent times after companies automated many of these processes and machine learning became popular.. But nevertheless, there are still many roles that will have more than 50% work on reporting and the rest of the role on answering the question: “Why did the event happen?”.
This is a good role to start your career in the analytics industry. But in the long run, must take the initiative and assume a role focused on “What is happening now?” namely, Business Intelligence / panelA panel is a group of experts that meets to discuss and analyze a specific topic. These forums are common at conferences, seminars and public debates, where participants share their knowledge and perspectives. Panels can address a variety of areas, from science to politics, and its objective is to encourage the exchange of ideas and critical reflection among the attendees...., or focused on “What will happen next?” namely, predictive analytics.
Intermediate analysis roles
This is the type of role that I started my career with. Most economics graduates / Statistics / Informatics will begin their journey with these roles. This is an optimal combination of business and analytics. It's a great way to understand the best of both worlds.
The roles in the field of intermediate analytics are also quite diverse. An extreme role in this category will focus on Business Intelligence trying to solve “What is happening now?”. The other end of this category will be highly business-focused roles., such as product pricing, in which you have to create many business scenarios and find the optimal price for the products that your company sells.
Most roles strike a more optimal balance between knowing the business and working with cutting-edge tools like deep learning in decision management. / risk analysis / fraud analysis. Most of these roles are involved in automated decision making. For instance, You may be tasked with creating an algorithm that can accept or reject credit card applications based on the customer's risk profile, or that you can select clients who have a high propensity to opt for a cross-sell offer of an insurance product. . All of these business problems require you to create predictive models on bulk customer profiles and rank them based on some business metrics..
If you are in this group, almost all your options will be open. Now you can choose to move into a more strategic role or you can choose to become a data scientist. In case you don't know where to go next, a good way to find your fit is to take a paper on the border of the two boxes. For instance, if you want to take on a strategic role in the future, you can test your fit by assuming a role in an intermediate analysis role based on profit and loss such as product pricing. There are a few more roles, such as portfolio analysis, that you can choose to familiarize yourself with the strategic roles. Keep in mind that you may have to live without data science techniques like deep learning if you choose to advance down the path of strategic roles..
Secondly, if you want to test your suitability as a data scientist, can take on business-embedded data scientist roles rather than pure data scientist roles. This way, you don't need to lose control of the business before moving down the path of research-oriented roles.
Apart from the two previous ways, has one more way to find a good trade-off between business and analytics: Roles de Tech Product Manager. But these roles are not readily available in the industry.. Companies primarily use data science to find a competitive advantage over other companies by creating data-backed strategies.
Tech companies like Google and Facebook use analytics not only to develop strategies, but also to create products. For instance, Google Instant Search is a technology product that uses machine learning to provide search results. These tech companies are looking for people with a skill set in both business profit and loss and machine learning to design such products.. If you choose to go ahead on this path, You shouldn't just apply to the big tech giants, but you should also look for product manager roles in niche skills companies like NICE, Aspect o Interactions.
Strategy roles
You may have heard of an important economic principle: “no economic benefits in a competitive market”:
The existence of economic benefits attracts entry, economic losses lead to exit and, in long-term equilibrium, companies in a perfectly competitive industry will reap zero economic benefits.
If all companies are in a perfect competitive market, How do they earn money? If you are an economics student, you will know the answer well. All successful businesses are based on market inefficiencies, so there is no one “perfect competition”. The role of a strategist is to identify these imperfections and nurture them to run a successful business. For large companies, we have strategists both at corporate and business level.
Corporate strategy is when you work at the corporate level answering questions like “What is the right business portfolio for your company?”, “To get to this portfolio, What new businesses do you need to acquire / to invest / growing up / to close?”, "What is the appropriate organizational structure for your business that will foster synergies in operations and other domains?”. For instance, if you work for Wells Fargo corporate strategy, develop a strategy to acquire or close deals as investments / Retail banking / Credit cards; you will also work on creating global operations to eliminate operating costs for individual companies, etc.
Business strategy is more linked to a particular line of business. While corporate strategy may be more focused on the expense side at the corporate level, business strategy is much more focused on maximizing net income. For instance, Wells Fargo credit card strategists could focus on maximizing revenue from their card customers. Many operations can be a shared asset across all Well Fargo lines of business, like call centers, chat centers, branch offices, etc. Therefore, these expense managers are better optimized at the corporate level than at the commercial level. The distribution of responsibilities may differ between companies, but most business and corporate strategists work hand in hand.
Both roles will require you to calculate the benefits of changes to a product's features., process change and technology investments by creating various business scenarios and calculating the net present value of different investments. Analytics professionals are well suited for these roles due to their knowledge of numbers and their deep understanding of the latest technology that will be used to create competitive advantage.. Analytical professionals who began their careers before 2010 currently constitute a large proportion of the population in strategic roles.
Roles of data scientists
Coming to the most fascinating role for most people looking to get into data science. The data scientist role is a specialist position. You can specialize in different types of skills like voice analysis, text analysis (PNL), image processing, Video Processing, drug simulations, material simulation, etc. Each of these specialist roles are very limited in number and, Thus, the value of such a specialist is immense. This is why we are seeing such high demand for data scientists these days..
To excel in these roles, must stay up-to-date with the latest tools and technologies. You should also invest in training yourself in relevant languages and have the ability to explain their complex models in simple terms to clients and companies. You can always go back to the strategy side in case you feel the need to understand the business concepts.
Final notes
The career paths mentioned in this article are based on my personal experience and a series of discussions I had with successful professionals in various fields of analytics.. With all the resources available online for FREE, you can easily migrate to any position you want with the right strategy. I hope this article has helped you define your career path.
If you have any ideas or suggestions on the subject, let me know in the comments below.
