How to Develop a Data Science Training Program in an OrganizationCategory: Data Science Posted:Feb 13, 2019 By: Serena Josh
Nowadays, the data-driven decision making is gaining popularity, and thus the job of Data scientist has become a new development all over the world. Most of the companies no matter whether it is big or small are searching for employees who can recognize and analyze the data. The data scientist has already been declared as the sizzling job; data scientist carries skill sets and knowledge from different backgrounds like Mathematics, Statistics, Analytics, Modeling, and business insight. With the help of these skills, the data scientists can find the patterns which in turn assist the organization to identify new market prospects.
But finding an experienced data science professional would be a challenge for the organization. Thus, many organizations are providing training to the current workforce with skills for data science work to bridge the skill gaps. A recent report has been presented on the increasing demand for data scientists; IBM predicted that by 2020, there will be around 2.7 million job opportunities for data science experts. According to Glassdoor, the average salary of data science professionals is $96,441 and much higher in some cities. As the demand grows, it is difficult to find a suitable candidate with appropriate skills, the organizations are struggling in recruiting data science expert; therefore the companies are following cross-training strategy to train the internal IT staff. As per a current report from data science community Kaggle, around 59% of employed data scientists obtained their expertise from self-guided learning or open online courses.
In order to train the employees in data science, the organization has to take a few essential steps. Let us have a look at the below steps:
1. Investigate the task and skills gaps in your company’s projects: The best way to start this is to visit with the project managers who take care of big data and analytics, and ask some questions to them regarding their project such as where are their projects deficits? In which project role they are facing trouble in staffing? What particular are technical and personal skills required? Are any project tasks getting hindered as there is a lack of experts to perform them? Thus, according to your research, you can compile a list of task and skills gaps by the project.
2. Co-relate your research skills needs with the internal staff: Once you have completed with the research, the next step is to evaluate internal employees to see who has the correct talent and background to move into these tasks and abilities gaps and then recognize them as trainees. This can be done by finding at individual IT experience with the company and researching employees past work experience. It is equally essential to visit with project managers to know more about the persons who are being considered and about their talents and interests.
3. Create a curriculum and find a project: The next step is to develop a prospectus and find a project. Well, it does not work to make the selected workers just work on skills development in a remote lab setting. Labs are useful for developing skills, but what makes these acquired skills, utilize them for applying them in real projects, where employees can create experience and self-confidence.
4. Regularly connect with Project Managers: Keep in touch with the project managers where newly-trained workers are organized so that you can observe how it is going on. This helps you in developing relationships with managers. It is also useful in assessing the success of training and abilities transfer by meeting with project managers after projects have been completed. It is expected to find the areas in your curriculum where training went fine, and other regions where it can be strengthened.
5. Review the curriculum continuously to keep up with real-world project needs: Most of the project requirements will remain comparatively steady whereas others will change according to the technology and business modifications. It is important, if you are developing training, keeping step with these modifications your training always provides the skills education as per the requirement of your project. You can confirm this consistency by continuously assessing projects, and then going back to your curriculum to confirm that the training is in sync with project requirements.
Well, there are various reasons due to which the candidates want to make their career in data science. Let’s explore them in detail:
1. The growing demand for data scientist: The data scientist job is creating publicity all around the world by its application. According to a report given by McKinsey and Company, by the end of 2020, there will be around 140,000 to 180,000 data scientist who is less than the required. The demand for a data scientist is ever growing, but the supply is very less. As compared to engineers and chartered accountants India needs more than 200,000 data scientist by 2020.
2. Data Science is an emerging field: Due to the growing demand of data all around the world, data science is growing rapidly. Data scientists have a wide assortment of ranges of skills that can use the information and data to assist associations in making better business decisions. They can get inspired motivating chances to work and explore different avenues regarding data to create the appropriate answers for the organizations. There are numerous new exciting fields which are also evolving in data science. This includes Big Data, Artificial Intelligence, and Machine Learning along with some recent technologies such as Blockchain, edge computing, Serverless Computing, Digital Twins, and others which engage various practices and approaches within the Data Science industry.
3. High ranging salary: As per a report from the Glassdoor, in 2016 data science was the highest paid field to start a career. According to their research, the national average salary for a Data scientist is around INR 6, 50,000 in India and the national average salary is $1, 20,931 in the United States. Thus, as compared to other jobs, these salaries are much higher.
4. Data Scientists give importance to the Business: Data scientists are flourishing in almost every field of businesses ranging from IT to health-care, from E-commerce to marketing and retail. As data is the critical asset of any company, data scientists play an essential role they serve as a trusted adviser and strategic partner to their management. They are responsible for examining the data for a treasured resource which support to enhance their niche, recognize the preferred target viewers and handle future marketing and development policies.
5. Easy to take a job: Data science is a booming field, and it is the most demanding job of this year. Most of the companies are greatly looking for data scientists because the demand for a data scientist is high and the supply is very less. Not only E-commerce companies are recruiting data scientist, but the companies from almost every field are appointing data scientists.
Data science is the emerging field which is not only assisting businesses to identify their markets and then making better decisions, but it is also enabling companies to get nearer to their clients to bring them effective services. The demand for a data scientist is increasing day by day. Most of the organizations are facing some challenges to find qualified data science experts as there are less talented candidates in this particular field. Thus, the organizations are arranging the internal training for their current employees to train them in data science and cover the skill gaps.
Got any questions for us? Please mention it in the comments section and we will return it to you. At ZaranTech we offer a self-paced online training program for Data Science and various other topics. Skyrocket your career by learning from the best! You can also visit our website for more engaging and informative articles.
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