Peter Sondergaard, a Gartner analyst predicts that “Every Big Data related role in the U.S. will create employment for 3 people outside of IT. So in the next 3 years, a total of 6 million jobs will be generated by the information economy.”
According to Gartner, data science is top business priority in 2015 and there are several options for people interested to pursue a career in working with data. If you are among those individuals interested in exploring a career with big data, the two major exponentially growing career options that you have are data scientist and big data developer.
For all the big data professionals who have the required technical expertise for enabling a company’s big data initiative- this is an incredibly advantageous time. With demand for big data talent booming, professionals can enjoy having an upper hand as they make best use of their skills in an organization they love working at. But the most important question – “How do you know what your dream companies are looking for when hiring data scientists and big data hadoop developers?”
We organized a DeZyre InSync session to answer this question through a live webinar on – “What Companies Hiring Data Scientists and Hadoop Developers are looking for?” We had the pleasure to invite industry expert Bob Kelly, Founder & Chief Recruiter at CareerPlanners to help professionals understand the recruiting dynamic in the big data space.
CareerPlanners Inc. is a recruiting company that helps big data companies find premium applicants for various big data job roles (data scientists, hadoop developers, hadoop administrators, data engineers, etc.) through effective search methods and extensive target advertising that can add value to the available big data hadoop job positions. CareerPlanners Inc. has worked with Cloudera, IBM, MapR, SAP, and Hortonworks. CareerPlanners Inc. has customers and partners from various industrial sectors like –social media (Match.com), Oil and Gas, Agero, etc.
You can click on the link below to listen to a recording of the recent webinar on “What Companies Hiring Data Scientists and Hadoop Developers are looking for?” by Bob Kelly.
The webinar discusses about-
- “Companies hiring data scientists and big data developers”
- Various hiring strategies companies use.
- How to prepare for data science or big data developer related interviews?
The foremost step to land a top gig as a data scientist or a hadoop developer is to choose the company. Professionals need to find out “Which companies are looking to hire?” The best way to do this is look around various job portals and newspapers to find out which industries are hiring big data professionals.Whenever there is news about acquisitions, take overs or any other such business information in various industries- there are increased job opportunities for big data professionals. Professionals can choose a company based on their area of interest, the industry they would like to work in, their preferred workplace location and the size of the company. All these parameters should be aligned with the overall goal of the individual based on their previous background and experiences.
Data Scientists can find increased number of opportunities in various industrial sectors like Retail, Health, Oil &Gas, Energy, etc. Data scientists should focus on working at a company that makes the best use of their business acumen. There are several websites like datajobs.com which list good number of big data positions for the job role of hadoop developers, data scientists, data analysts and data engineers in US and across the world.
Strategies to Use on Hiring Managers
- Professionals should demonstrate the eagerness and enthusiasm to the hiring managers or recruiters for an open big data job position. They need to differentiate themselves from other people on the list of hiring managers.
- Professionals attending interviews for big data or data science jobs should do their homework thoroughly- get some knowledge on the company profile, understand the industry the company is related to, try to understand the kind of data problems the company is trying to solve, etc.
- If an individual has worked on similar data problems the company is tackling, then it is always suggested that during the interview you open up the challenges that you have faced while solving such data problems and how you tackled them.
- At the end of the interview just do not walk out saying that you are done. The hiring managers always give the applicants an opportunity to ask questions. This is the time when applicants can make the recruiter or hiring manager understand that you are the best fit for the job who can start immediatelywithin the timeframe they want and accomplish it within the company’s allowed budget.
- Applicants must ask the recruiters or the hiring manager- how they know they have got the right candidate for the open big data position in their company.Ask the recruiter what the company needs to see within X number of days after hiring a candidate-the company might expect the right candidate to establish a working dialog between various departments of an organization within a stipulated time or they might want to build an enterprise architecture within 120 days or any other task that is bound by time frame. Applicants must not merely boast of their years of experience but rather try to understand what is that the company actually needs in the right candidate to get the job done.
- Applicants must not depend on the hiring managers or recruiters for getting a job because no recruiter or hiring manager will take the job as seriously as the applicant. Recruiters do help but relying on them completely is not the best way to get the job.
- Networking is the most common way that has helped people get most of the big data jobs. Applicants must leverage their networks through LinkedIn, Twitter, to stay up-to-date with the latest job openings and also to get noticed by the recruiters.
Data Science or Big Data Developer Interviews
Hiring managers or recruiters for big data job positions have specific requirements for a particular job opening and each one needs a different candidate. Some might consider experience as a priority, for some technologies known could be a priority or understanding of the business acumen. The applicants must understand what they need- do they need people who have worked with real time systems or people who are back end oriented or front end experts,etc.
Recruiters look at your resume to understand your strengths and weaknesses. Applicants must be prepared to address their weaknesses when questioned. For instance , if a person does not have sufficient experience- he/she can demonstrate to the recruiter that they have accomplished a task based on client requirements within the given time frame even without X years of experience which is required to do the job. You need to convince the recruiters that you are the best fit for the job even if you do not have the required experience. Map your background with the requirements of the recruiter.
Advice for Beginning your Journey into Data Science-
- For people who are just beginning with their career in data science and have solid academic foundation- they need to develop their business domain knowledge. People who come from academic side, lack of business acumen can prove to be a hurdle in getting the job because recruiters are looking for people who can correlate data with real world applications.
- Applicants must be quick enough to switch over their analysis tools. If you are working with excel for analysis, be prepared to switch over and master another tool quickly. They don’t need people with excels as their workhorse but rather need people who are experts with Hadoop , Python Language, R Language , SAS, etc.However, just knowing these tools will not help you get a data scientist job as it requires a broader skill set.
- For a data scientist, visualization plays a vital role and a person who can effectively communicate their data findings to the users will appeal to the recruiter. Business users are not data geeks, data scientists should clearly help them visualize the context in an understandable manner with the help of various tools on how data can help them solve complex problems.
- A study revealed that 46% of data scientists have Ph.D. and 88% of data scientists have a Master’s degree. These are just the findings and this does mean that if you possess a bachelor’s degree you cannot get a data scientist job. It all depends on your skills and expertise and requirements of the recruiters.
Data Scientist Salary Breakdown
- Salary range for an entry level data analyst ( a data scientist in-training) is $50K to $75K whereas for experienced professionals it is in the range of $65K to $110K.The salary depends on your aptitude skills and your ability to solve data problems.
- Salary range for experienced data scientist who possess expertise in statistics and machine learning is $85K to $170K.Under unique situations, for people experienced in advanced algorithmic development of hedge funds the salary can be as high as $250K.
- Data engineers or hadoop administrators who setup and configure systems or hadoop clusters have salary range from $70K to $115K or beyond this.
- Big Data Engineers with excellent domain expertise command salaries in the range of $100L to $165K which varies based on the seniority, depth of experience in particular subjects like real time systems, MongoDB, Cassandra, Memcach, etc.Candidates with technical accomplishments and more certifications often have edge over others in the eyes of hiring managers.
All these salaries are excluding the bonuses and have been taken from the survey findings of datajobs.com.
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Applicants must not focus on the money but lay emphasis on the job opportunity and what career growth it can bring in the future. Recruiters don’t want to make a bad hire because it can be a costly affair, thus applicants must get a clear picture on what the company needs. The goal of hiring mangers is to hire people who are interested in the job and have the capability to grow in a particular big data position by making a positive impact on the company. Remember, hiring managers are not looking for unicorns, ninjas, pirates, 10x data scientist or Master’s degree they need people of all ethnicities, genders and backgrounds who can effectively solve the data problem a company has.
Everybody wants to make the most of data science discipline. DeZyre helps create better enterprise data scientists through IBM certified data science courses which helps professionals put data science discipline into practice.
Please share your big data and data science interview practices and experiences in the comments below.