Categories: Data Science

5 Data Science Trends All Aspiring Professionals Need to Know

Data scientists are tasked with sifting through large amounts of data — much of it unstructured — to procure insights that decision makers rely on to improve business operations. Being a data scientist is a multifarious field that requires a unique and versatile skillset. Top data scientists are more than just data hunters; they are analysts, visualizers, testers, architects and more.

Skillsets such as these are rewarded with a handsome salary range that averages $120,000 per year in the U.S, according to Glassdoor, which also ranks it in the top 50 for best Jobs in the America.

There ‘s no question that careers in data science will remain a hot prospect well into the future. If you want to take advantage of everything that a career in this sector has to offer, make sure you are aware of these following five data science trends. They can help you advance your career even faster—resulting in more lucrative pay and perks just for staying ahead of the curve.

No. 1: Multiple Career Sectors

Data scientists are not restricted to just one industry. Rather, careers in data science are far reaching and are found in industries like financial services, logistics, social media, ecommerce, government and many others. Every business sector benefits from having a data scientist convert data into usable insights. As this trend continues, new sectors will open that increase the demand and pay for this career.

Perhaps the most demanding sector for data scientists is found in the financial services industry, where transactional and account data is reconciled in large amounts, and where data breaches can sometimes go undetected. Experts in this sector specialize in compliance and security as well as anti-fraud, detection and prevention.

When considering a career in data science, don ‘t restrict yourself to any one sector. The more open you are to different opportunities, the faster you ‘ll be able to advance your career.

No. 2. On the Job Learning

One thing that you can expect with a data science career is that there will be plenty of on the job learning required to meet the demands of your employer.

The ongoing development of skillsets necessary to meet industry standards is something that you ‘ll be able to pursue by taking professional courses, advancing your education with online classes, and by attending data science courses and online bootcamps. Along the way, you will also want to consider adding additional qualifications to your resume like a big data certification.

Upskilling will become one of one of the most important career trends in data science over next ten years. As technology continues to expand at a rapid pace, ongoing education will become the norm in this field. Staying ahead of the fold will require routine attendance in group meetups, seminars, online training and more to keep a healthy balance between on the job learning and offsite training.

No. 3 Data Analytics

Data analysts are high in demand and short in supply. A prominent reason is because businesses have a distinct need to sift through troves of unstructured data, parsing out the bad data and harnessing the insights that can be procured from the quality data.

Perhaps the most in demand skill for a data analyst as of the present is quantitative analysis, something that enables you to analyze large sets of unstructured and unfiltered data. This unique method helps scale overall data strategy while coinciding with advancing machine learning methods, AI and deep learning.

Ongoing education will help you take your career to new levels in data science. Being able to observe and apply new methods, disciplines and strategies for how you work with and manage large data sets will ultimately lead to increased job security and better pay.

No. 4: Business Intelligence Skills

The next wave of business intelligence is emerging, making it necessary for data scientists to be adept in this skillset. The ability to describe the data sets that you are working with while cultivating visual analytics and delivering critical insights to decision makers is what will separate you from the rest of the pack and make your work stand out.

Evolving communication skills are essential to a data scientist excelling at their job and being able to craft the necessary analytics and insights they ‘ve cultivated from data mining into their work. The balance of converting data rich sets, while also ensuring that the delivered work is concise, direct and non-technical, is where the real magic happens.

Hard skillsets that you ‘ll want to improve and master include SQL and Tablue—both of which will aid you with core data management and data visualization.

No. 5: Maintaining Technical Skills

The most prevalent of data science trends is the maintenance of your skillsets. Maintaining versatility with various technology platforms is critical to long-term success in this field.

Modeling platforms like Python, R and SAS have become industry standards. Meanwhile, Apache and Hadoop are popular frameworks. And NoSQL, MongoDB and HBase remain popular databases for high bandwidth entities.

Familiarity with data management tools such as Informatica, SSIS, ETL, Teradata, Power BI and IBM are all necessary elements to maintaining skillset diversity.

Without a doubt, data science is a complex and ever-evolving career. But with its innate challenges does also come the reward of a competitive salary, strong benefits and cushy perks. By staying ahead of the curve and keeping these common data science trends in mind, you ‘ll be able to sustain long term success.

Nicole Nelson

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