Just a decade earlier, storing and maintaining data was a nightmare: there weren’t enough processes, inadequate infrastructure, and the lack of technological know-how to create that data into valuable information. However, with rapid technological advancements, we now live in a data rich environment. Around 2.5 quintillion bytes of data is generated and processed every day. Even the AI/ML algorithms have matured slowly to process this data. Therefore, it only seems fitting that data science is a job that has observed a high demand in the market lately.
Post 2020, hiring for a job in the field of data science is going to be especially challenging as the process requires rigorous assessment of technical skills. Since these jobs are in demand, the suitable candidates receive numerous lucrative offers, which reduces the success rate of hiring. To prevent this, companies needs to have a clear idea of what the organization needs and what are the expectations and strengths of each candidate.
Apart from this, hiring a data scientist is challenging process because the job description is often misleading. It is essential to address what problem you need to be solved by the candidate. For example, a candidate can be good at machine learning and not data analysis. In that case, even if the candidate performs well in the assessment, they would not be able to satisfy the job requirements. Hence, it is essential to have a crisp and clear job description.
Before hiring a data scientist, you need to assess the use of data science in the organization. Data science has proven to solve several of business problems. Data science has proven to improve customer retention, it also proven to improve the internal processes. Data science shows insights on how people use your products; therefore, it helps in product development and helps in targeting customers at the right time. Another benefit is that it aids marketing on social media by analyzing customer sentiments. It also helps in financial modeling, i.e., building a model of a real-world financial situation.
What are the job roles that require data science skills?
1. Data Analyst: A data analyst focuses on the analysis and solving the problems related to data, types of data, and the relationship between different data elements within a business or IT system.
2. Data Engineers: Their main role is to build data pipelines to pull together information from different source systems; integrating, consolidating and cleansing data; and structuring it for use in individual analytics applications.
3. Machine Learning Engineer: ML engineers are programmers that create programs to enable machines and systems to learn and apply knowledge without any specific direction.
4. Data Scientist: A data scientist analyzes and interprets complex digital data, like the usage statistics of a website and to assist a business in its decision making.
5. Data Architect: A data architect is a practitioner of data architecture, a data management discipline concerned with designing, creating, deploying, and managing an organization's data architecture.
6. Business Analyst: A business analyst (BA) analyzes an organization’s business domain and documents, its business or processes or systems, and assesses the business model or its integration with technology.
7. Database Administrator: A database administrator is a specialized computer systems administrator who maintains a successful database environment by directing or performing all related activities to keep the data secure.
8. Statistician: Statistical analysis is the process of generating statistics from stored data and analyzing the results to deduce or infer meaning about the underlying dataset or the reality that it attempts to describe.
9. Data and Analytics Manager: They provide direction to the team of data analysts. They also decide as per their experience where each analyst’s skills will help improve the organization’s productivity. They also oversee the analytics department, making sure the reports generated are accurate.
How Interview mocha is helping in assessment of candidates for jobs in data science?
To conduct an online skill assessment, firstly we need to understand what are core data science skills that need to be assessed in a candidate. There are three main domains of skills that need to be assessed in a candidate applying for a job in data science:
1. Technical skills: These are the most important skills a candidate must possess. Skills like SQL, Python, R program, and apache spark are considered as important technical skills required for a job in data science.
2. Domain knowledge: Another requirement of a job in data science is that a candidate must have a sound knowledge of domains like machine learning algorithms, data extraction and mining algorithms, data wrangling, deep learning.
3. Mathematics and statistics: These are necessary for every job in data science. A candidate must have good knowledge of statistics and mathematics as it is required for jobs related to machine learning and statistical modelling.
Most of the data scientists do not possess expertise in all three domains. Hence, it is essential to prioritize based on the needs of your organization, hire experts that are proficient one or two of these skills and assign jobs accordingly.
Interview Mocha has divided its skills library in 6 parts. Here are the tests that Interview Mocha has in each part of its skills library:
1. Computer science: Python, Java, SQL, Hadoop, Apache spark, data structure, and algorithms, etc.
2. Supervised learning: Regression algorithms, decision trees, KNN, etc.
3. Unsupervised learning: Clustering algorithms, K- means algorithms, and Apriori algorithm.
4. Mathematics and statistics: Statistical modelling, statistics for machine learning, etc.
5. Code simulations: Code simulations are available on Scikit learns, pandas, NumPy, matplotlib, etc.
6.Machine learning concepts: Data exploration, data pipeline, pattern recognition, anomaly detection, etc.
After the assessment, a detailed report is generated. The report includes section-wise score, skill proficiency analysis, question level analytics, code reply, and proctoring details. The skill test is highly customizable. The test can be created, and any type of questions can be added to as per the choice of assessor.
The skill assessment test also has a proctoring feature where images of a candidate are recorded to check for any violations. Hiring a data scientist can be difficult and challenging after 2020. However, with online skill assessment tools like Interview Mocha the process has not just become simpler but better. We recently conducted a webinar on How to assess and hire data scientists in 2020, you can watch the webinar here.