Landing an interview for a data scientist position is exciting. But it can also be a bit anxiety-inducing, particularly if you are worried about how you compare to other candidates. Often, every interview is going to have a similar technical skillset, so you can’t necessarily rely on your data science know-how alone. Instead, you have to figure out what makes you unique and how you can provide the employer with value.
While that may seem daunting, it isn’t as difficult as it appears. If you want to stand out in your data scientist interview, here’s what you need to do.
More companies than ever before are embracing their data, leveraging it to make smarter business decisions and help them learn about the customer base. Data analytics plays a large role in maximizing the value of data, and 2018 is poised for some major advancements.
However, it isn’t all sunshine and rainbows, particularly if you are just venturing into this exciting arena. To help you prepare, here is a look at what IT leaders can expect from data analytics this year.
Cloud Computing is Essential
Based on the sheer volume of data most organizations have managed to gather, on-premises solutions may not be sufficient for supporting data analytics goals. This makes cloud-based solutions critical, as they allow for greater flexibility and scalability, while also promoting collaboration.
Cloud computing infrastructure is often far more capable when it comes to managing increasing quantities of data, and the ability to select new tools and models to implement is easier on the cloud, particularly from an operational perspective. Plus, the increased level of agility makes exploring emerging solutions simpler, as many internal infrastructure limitations aren’t a factor.
Growth is Possible
Data analytics has the ability to support business growth in a variety of ways. Not only can it help companies increase their profits through a deeper understanding of customer preferences and behavior, but it can also assist with streamlining internal processes, modeling the results from potential solutions, and improving engagement. The technology is particularly effective at identifying bottlenecks in production, allowing companies to focus on key areas that will result in the most significant level of improvement.
Cumulatively, this allows organizations to develop innovative solutions based on concrete data, increasing the likelihood that any changes will be effective.
While data analytics solutions can be quite robust, that doesn’t guarantee a seamless deployment. Some companies aren’t realistic about their expectations, often due to a limited understanding of the technology, and securing top talent to manage the workload can be difficult.
Often, successful data analytics deployments involve a number of different skill sets, including those traditionally held by business analysts, data analysts, modelers, and engineers. In some cases, AI and machine learning specialists may also be required, depending on if you intend to leverage those technologies in conjunction with data analytics. When viewed together, this can seem like a tall order, especially if you don’t already have some talented individuals on your team.
However, IT leaders can mitigate these concerns by ensuring that all stakeholders are fully aware of both the benefits and limitations of data analytics. Additionally, by securing the right employees, you can make sure that your team has the necessary skill set to maximize the value of data analytics at your business.
If you are looking for a data analytics professional, the knowledgeable staff at The Armada Group can connect you with some of today’s top talent. Contact us today to see how our services can work for you.
Big data and analytics are among the hottest areas in computing now. Companies are capturing more data than ever: data used by their information processing systems; data generated by Internet of Things sensor-based devices; data that tracks every customer interaction with their website – even the unstructured reviews and comments their customers post on Facebook and online forums.
Then they combine that data with data from third-party sources, like weather forecasts and economic trends, and use statistical methods, machine learning, and other analytics to find patterns and make predictions to help them run their business more effectively, make more sales, and generate more profits.
One result of the growth in data is corresponding growth in data-oriented jobs. These jobs range from data engineers, who focus on putting in place the infrastructure for managing mega-sized data collections, and the data analysts and data scientists who turn the data into insight.
Because the demand for data-wrangling pros is so high, technical staff with data skills, such as SQL, NoSQL, Hadoop, Python, data visualization, data mining, and machine learning earn correspondingly high salaries.
Job sites report average data analyst salaries of $87,000 for jobs in Silicon Valley, significantly higher than similar jobs in other locations. Experience adds to your value and your paycheck, with average salaries around $120,000. The data engineer title in Silicon Valley can earn an even higher salary, around $145,000. Senior data warehouse engineer salaries in Silicon Valley can exceed $150,000. If you've got the skills for the data scientist job title—which typically requires a master's or Ph.D. in data science, analytics, machine learning, statistics, or applied mathematics—you can ultimately command a salary up to $250,000.
Of course, commanding those salaries requires having the skills to produce corresponding value for the company. If your education and experience support your ability to do this work, The Armada Group can connect you with opportunities that will challenge and reward you. Contact us to let our recruiters help you turn data into profit.