According to the latest studies conducted by Harvard and Bloomberg, the Data Scientist remains to be the sexiest profession. The question that arises is what exactly makes this profession an attractive position. Every business has some fish to fry in this stream, it is because of educated and precise decision-making to be executed in their marketing strategy. The interviewers generally look for a candidate who has outstanding technical skills with adequate management knowledge.
Data Science is more of a lifestyle than a profession. The person over time has to develop key qualities required to excel in this career. This article will be dealing with the technical aspect of the interview question. For soft skills please refer to another topic with Data Science Soft Skills. Data science works on the principles of Machine Learning which can be broadly characterized into two categories- Supervised Learning and Unsupervised Learning.
Data science deals with algorithms that synthesize data and based on the scope of work give the desired outcome. Supervised and Unsupervised as the name suggests is a kind of learning that helps algorithms to make wise analyses. None of them is superior to one another. Supervised learning is used for the prediction of outcomes whereas unsupervised learning is used for the analysis. Supervised learning deals with the structured and labeled data but unsupervised learning is used only with unlabeled data.
Supervised Learning is like learning with the help of a teacher. The two most commonly used case scenarios for Supervised Learning are - Classification and Regression.
Unsupervised learning is like learning without a teacher. When the learning is done without supervision, multiple faces of outcomes appear which helps in deepening the concepts and increases the curiosity. Similarly, Unsupervised learning in Machine Learning is a division where data sets are provided but without any labels. Therefore machine on itself with identify similar patterns and surface some key findings.
Bias as the name suggests are prejudiced assumptions. The machine learning model is made extremely similar to the human brain. As we humans with our own bias assume things and reach the conclusion similarly machine learning also does the same thing. Our assumption is simply carried by past experiences that have some similarities to the current situation. These biases help us in making an educated yet informed decision and often decrease the time taken in reaching the verdict. The resemblance of the verdict with the real world is highly dependant on the education of bias.
In Machine Learning before reaching the conclusion or desired result, the algorithm predicts some biases by simulating the real-world scenarios. These biases are the main reasons that why the outcome in the Machine Learning algorithms always differs. There are two ways of executing biases in Machine learning- High Bias level, Low Bias level. The number indicates the new concepts learned by the algorithm. However, it can also lead to inconsistency and too much variance in the result received. Therefore it also implies the degree of intelligence of an algorithm in taking the right decision.
Data science is the mathematical modeling of data by applied intelligence and under the supervision of machine learning rules. Machine Learning of Data Science is capable to do the job of more than 100 individuals alone without 99% accuracy. Technical skills are the primary aspect of clearing a Data Science Interview. However, there are some soft skills that every data scientist should be focusing on to get better at explaining the intricacies of the result obtained. A well-articulated solved problem will influence each and every person in the room.
An average data scientist in India makes around 10 Lac INR per annum. In order to make yourself worthy of this package and lucrative job description, soft skills are extremely important. The machine will definitely do its task efficiently but it is the responsibility of the Data Scientist to explain the interesting linkages in a form of an aspiring storytelling way.
For any Data Science job, technical skills are the topmost priority. Therefore at EdifyPath, we have a course specifically designed to solve all the technical properties. There's also a mentor assist program wherein a real-life scenario will be implicated. These real-life scenarios are replicated and the students with the help of a mentor have to arrive at the desired outcome.
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