I am sure by now you know that Data Science has been consistently called as the hottest job on the planet. With the huge buzz, we are already seeing a big increase in data science training courses, university level graduate courses and Google search volume for “data scientist jobs”.
Google Trends: Data Science Jobs
This tells me in order to land a big data analytics job, I need to study data science. There are many people who think “I can have a big data career only if I get a data science degree”.
Quite honestly this is far from the truth and by the end of this post, I can prove it to you. If you are serious about landing a career in big data analytics, then continue reading as I take you through 7 big data career choices other than data science.
Career opportunities listed in this post:
#1 Customer/User Experience Designer (Median pay $73,162 source: Payscale.com)
#2 Business/Marketing Analyst (Median pay $50,868 source: Payscale.com)
#3 Customer Relationship Management (CRM) Analyst (Median pay $51,802 source: Payscale.com)
#4 Ecommerce Manager (Median pay $63,106 source: Payscale.com)
#5 Campaign Manager (Median pay $53,813 source: Payscale.com)
#6 Hadoop Developer (Median pay $90,208 source: Glassdoor.com)
#7 Big Data Architect (Median pay $124,208 source: Glassdoor.com)
Customer Relationship Management and Big Data
In 2012, IBM did a study called “Analytics: the real-world use of big data”. The purpose of the study was to identify how organizations big or small are using or planning to use big data analytics. The study was an eye opener as 49% of the businesses identified customer centric objective as a top priority. If you closely look at this research, you will see three customer centric areas where businesses are betting on big data:
1. Improve overall customer experience
2. Understand customers holistically
3. Personalize customer journey
Source: Analytics: The real-world use of big data by the IBM Institute for Business Value and the Saïd Business School at the University of Oxford
So let’s looks investigate each customer centric objectives:
1. Improve customer experience
Enough has been said about how customer experience is the key to successful business outcomes. When I hear business worrying about conversion, my first ask to them is to focus on the customer experience. We live in the design age, and our expectations continue to rise as Apple and Samsung battle to deliver top notch design experience in our hands. I love my iPhone and I think of my experience on every website in terms of the easy of use and awesomeness of my phone.
When it comes to delivering top notch experience, businesses are leaving no stones unturned. This gives an opportunity for the UX/UI designer to step in and leverage data to drive experience.
Graphic designers of today are not the forgotten flip-flop wearing dude sitting in their basement (already I am sure they still are :)). User experience and crow sourcing have allowed the designers to shine and showcase their talent. If you are a designer looking for career boost, you can submit your design to Awwards.com and Behance.net and win a design contest.
So how can designers work with big data? If you know how to use tools to connect business objectives to user design and solve customer struggles, then you are already a data player. Organizations are looking for experience designers with skills to run UX analysis using tools such as Tealeaf and Clicktale. Both tools can help you surface customer struggles (design and technical). If you are starting a new design project, ask yourself these questions:
What is the key objective of this creative design?
How can I improve what’s already been done on this project?
In fact, one study I came across showed how more than half of the customers left the digital property due to bad experience. Imagine losing half of your customers because of bad design.
49% user left site after poor experience
If you continue to add data skills to your profile, you will be quickly approached by your customer analysis group or land a job in the customer experiments group.
2. Understand customers holistically
If you follow my blog then you may remember in my digital marketing habits post, I called out the 40/20/30/10 rule: 40% analysis, 20% planning, 30% execution, 10% reporting. While this was specifically for digital marketers, the same logic applies to a wide variety of job types. The point I am making here analysis should be core part of the work that involves data.
Understanding the customers is one such big data project where analysis is the key, and it opens up several opportunities.
Marketing analysis may seem to be a traditional job function in the marketing department but the stakes for an analyst have been raised. The reason I say this because the dramatic increase in the channels, devices and touch points has allowed marketers to elevate their data problem as a big data issue.
At its core, the job function of an analyst consists of these three-steps, which I call the “trifecta of analytics” (i.e., collect, analyze, and evangelize). While all three are crucial, for me the most important step is to analyze the data and understand the customers effectively. I would not have said this 10 years ago but today the analysis step presents new challenges with the never-ending flow of social media data. If you pair the social data with the digital analytics data feed and sprinkle user behavior data, then you could easily be in the “terabyte” fairly land.
Trifecta of analytics
I encourage you to talk to recruiters looking for marketing analyst, and they will tell you how hiring managers are keen about big data analysis capabilities. To further validate this, a recent study by IBM reveals that about 94% of CMOs plan to use “advanced (predictive) analytics” technology more extensively.
The CMO study I mentioned earlier also shows how CMOs are interested in using technology to manage CRM. Customer data analysis for reducing churn has been a widely accepted use case of predictive analytics, but lately it has gained more momentum. Marketing leaders are looking for CRM analyst who can manage complex analytical tools to predict churn, forecast NPS (Net promoter score) trends and loyalty, perform RFM (recency, frequency and monetary value) analysis and identify profitable customer segments. The CRM analysis will get more complex as CRM analysts start utilizing social media data for developing customer segmentation and predictions.
CMO insights from the Global C-suite Study by IBM
3. Personalize customer journey
You would think the analysis of customer journey is the end to the problem, but actually it’s just the beginning. Although with customer journey analysis, you can uncover user experience flaws, the real challenge is delivering a consistent personalized experience across the customer journey. I still remember the time when personalization basically meant having the receiver’s first or last name in the email subject line or landing page.
Email subject line personalization
While the technique is still used by businesses, it is not remotely close to how data has influenced personalization. Amazon is the leader in delivering personalized experience using big data analytics. Its product recommendation engine is the foundation of the entire product recommendation industry. Netflix is another company and I truly appreciate it’s algorithm that drives recommendations to improve customer experience, most recently with real-time processing.
Netflix personalized recommendations
Let’s look at some of the jobs where data-driven campaigns and personalization is used.
There are 11,327 e-commerce manager job listings on LinkedIn and 6,629 jobs on Indeed.com. This data is limited to only two networks, but it is fair to assume e-commerce managers are in great demand. Ecomm manager’s daily responsibility has a lot to do with utilizing data to drive improve customer experience and loyalty. Here are few bullets pulled from 3M’s LinkedIn job post:
Leadership for 3M Consumer retail e-commerce, including practices in product presence, demand generation and analytics utilized to improve the sales of 3M Consumer products through pure play and multichannel retail partners, including Amazon.com, Global Amazon, Staples.com, OfficeDepot.com, Walmart.com, Target.com, and other accounts.
Follow identified best-practices and processes to improve product presence on e-commerce websites. This includes actively consulting and supporting the business team as they execute on account negotiations, SKU presence improvements, product detail page improvements, images, videos and rich content and other requisite best-practices to reach e-commerce sales goals.
Work closely with the Digital Asset Management team to identify best practices and processes to manage data and assets for e-commerce programs.
Partner with US Consumer business unit teams to define objectives in e-commerce, including product content, product positioning, website advertising and demand generation programs, channel strategy and competitive response.
You see, how by using data analysis to deliver personalized user experience is woven into this job category.
To retain and grow customers, e-commerce managers often tag team with campaign managers. Campaign manager’s core responsibility is to develop and launch marketing campaigns to either acquire and retain customers and increase revenue. Unlike marketing manager, campaign manager is focused on launching and running campaigns, and they heavily rely on customer experience and personalization to drive sales or leads.
Core Big Data Jobs (non data scientist)
Since we have already discussed customer centric jobs focused on big data it is equality important to discuss some of the core big data jobs. By core jobs, I meant jobs directly applicable to data mining, administration and development. Keep in mind these jobs require programming skills, knowledge of data platforms such as Hadoop, Cassandra or Hbase and/or experience with ETL tools such as Informatica or Talend.
I am seeing a big increase in the implementation of Hadoop technology and the demand for Hadoop professionals. Hadoop developer is a software developer specialized in Hadoop technology. If you are looking forward to develop Hadoop skills then here are the keywords you would want get familiar with:
– Java, Python, Pig, Hive, Hadoop Streaming, Sqoop, Oozie, etc.
– MapReduce and Hadoop Distributed File System (HDFS).
– SQL Relational Databases (RDBMS)
You can get your hands dirty with Hadoop very easily and here are three options:
Hadoop on PC/Mac (Follow instructions at Apache Hadoop)
Hadoop on virtual machine (Hortonworks has a good Hadoop product)
Hadoop in the cloud (Amazon, Google, IBM and HP offer cloud Mapreduce and Hadoop services)
The big data architect is the chief designer of the big data solutions. Organizations expect the architect to be a cross-functional leader of technology, framework and teams to get big data projects off to the ground. I see this as a more senior role for those who have been in the business for quite some time and have all the expertise needed to drive major data projects.
Big data industry is growing rapidly so I wanted to list the out the best entry point possible. To land a big data job you don’t need a data science degree, although you will need the business acumen for data leadership. If you are already in customer centric or marketing roles, you have better chance to add big data skills to your portfolio.
How do you plan to build your career?