Data Scientists ranked first among the most promising jobs in the United States in 2019 as per LinkedIn’s report. According to the same report, Data Scientists averaged US$130,000 in the basic salary this year. Furthermore, the job vacancies increased by 56 percent from the last year. Currently, there are more than 4,000 Data Science vacancies across the country. No wonder: Data Scientists are led to the top as the best job in the United States, thanks to its high demand, high salaries, and high job satisfaction. Also, Analytics India Magazine predicts that the demand for Data Science professionals in India will increase sevenfold in the next seven years and the market will reach US$20 billion.
Thus, it is a high time you made a transition into Data Science by enrolling yourself in a definitive Data Scientist course.
But first, let’s take a look at the skills and qualifications you must have in place before jumping the gun. Here is a quick overview of what this blog will be all about:
- Current Data Scientist Job Requirements
- Data Scientist Qualifications That Companies Look for in a Candidate
- Data Scientist Roles and Responsibilities:
Before delving into what the roles and responsibilities are of a Data Scientist, let us take a brief overlook on what companies expect from a Data Scientist.
Current Data Scientist Job Requirements
The following is a summary of the Data Scientist roles and responsibilities from major job portals, including Indeed and Glassdoor. As a Data Scientist, you have to:
- Work with stakeholders to determine how to use business data for valuable business solutions
- Search for ways to get new data sources and assess their accuracy
- Browse and analyze enterprise databases to simplify and improve product development, marketing techniques, and business processes
- Create custom data models and algorithms
- Use predictive models to improve customer experience, ad targeting, revenue generation, and more
- Develop the organization’s test model quality and A/B testing framework
- Coordinate with various technical/functional teams to implement models and monitor results
- Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy
Learn more about the most popular Data Scientist skills of 2019 with this blog
Data Scientist Qualifications Companies Look For in a Candidate
Data Scientist roles and responsibilities include identifying business trends and changes through advanced Big Data Analytics and using a variety of techniques to interpret results from multiple data sources through statistical analysis, data aggregation, and data mining. This is a very important role, and most companies expect some or all of the following Data Scientist skills in candidates before hiring them.
- A natural inclination toward solving complex problems
- Knowledge/experience on/with statistical programming languages, including R, Python, SLQ, etc., to process data and gain insights from it
- Experience using and developing data architectures
- Knowledge of Machine Learning techniques, including decision tree learning, clustering, artificial neural networks, etc., and their pros and cons
- Knowledge and application experience in advanced statistical techniques and concepts, including, regression, distribution properties, statistical testing, etc.
- Good communication skills to promote cross-team collaboration
- Impulse to learn and master new technologies
- Experience/knowledge in statistics and data mining techniques, including, random forest, GLM/regression, social network analysis, text mining, etc.
- Experience with major web services, including S3, Spark, Redshift, etc.
- Experience/knowledge in distributed data and computing tools, including, MapReduce, MySQL, Hadoop, Spark, Hive, etc.
- Ability to use data visualization tools to showcase data for stakeholders using D3, ggplot, Periscope, and more
Learn the key concepts of Data Science from this tutorial video:
What are some Data Scientist roles and responsibilities?
As a Data Scientist, you need to design, develop, and deploy the most relevant solutions for your business and share your results with stakeholders. This requires preparing Big Data, implementing relevant data models, and creating databases to support your business solution.
Analytics: Exploring Ways to Infer Relevancy in Data
Leveraging fast-growing data sources that can be used for capture and analysis is one of the biggest business challenges that market leaders face today. The amount of data getting generated every day is almost 2.5 quintillion bytes and the possibility of relevant data is also huge. Thus, regardless of whether the data is from a machine or from other sources, relevant analytics allows you to discover important information that would otherwise be hidden.
According to Indeed, the five most important skills for a Data Scientist listed in their job portal are:
- Machine learning
Nine out of ten jobs require at least Python, R, and/or SQL as important skills of a Data Scientist. According to the same report, these skills are closely related to the roles and responsibilities that aspiring Data Scientist should learn. Thus, these Data Scientist skills will make you eligible for almost 70% of all online positions in the Data Scientist’s role. Extending your Data Scientist roles and responsibilities beyond these will allow you to earn higher salaries.
In a data-driven organization, your stakeholders rely on you to help them make decisions. To do this, you need to know what, when, and how to use which machine algorithms. Your choice will make or break the answer to a business problem. Statistics provide the means/tools necessary to drill down into the data and gain valuable insights. The more statistics you know, the better will be your analysis and quantification of uncertainty in a dataset. Therefore, “analyzing data with statistical knowledge is one of the most critical Data Scientist roles and responsibilities to transforming yourself into a successful Data Scientist.
Go through this Data Science Tutorial to get a glimpse of how the Data Science learning journey would look like.
Collaboration with Stakeholders
A Data Scientist works with various database types to capture and process real-time distributed data. As a result, existing companies design and develop custom systems for capturing, managing, and retrieving data to support the analysis and dissection of complex and large datasets. As a Data Scientist:
- You will be responsible for supporting the development of computing resources and custom enterprise-level tools to be used by analysts, developers, and other professionals.
- Not only do you need to focus on developing computer systems, but you also need to work closely with stakeholders, CIOs, and other teams to develop various sorts of requirements.
- You must learn to design, develop, and implement the most appropriate solutions for your business and share them with your stakeholders. This requires preparing Big Data, creating databases, and implementing relevant data models.
Data Scientists work closely with marketers, decision-makers, and other stakeholders in their projects and products to channelize/communicate all possible outcomes. This type of collaboration has proven to be a huge achievement and is often considered one of the most important Data Scientist roles and responsibilities.
Business Understanding: Dealing with Business Problems and Finding the Best Solution
‘Data Scientists know more about statistics than any software developer and know more about software development than any statistician.’ Josh Wills, Director, Slack.
Data Scientists combine data, computing, and technology to gain valuable insights by leveraging the business levers available to them. They play leading roles in managing a range of business support projects that require them to leverage and synthesize large amounts of data to enhance a company’s trends and outcomes and decision points. Also, Data Scientists are responsible for:
- Advising companies on data potential
- Gaining new insights and transforming them into business goals
- Developing solutions that improve business performance through advanced statistical analysis, data mining, and data visualization technologies.
Strategy/Design: Interacting with In-house Teams and Customers
One of the Data Scientist roles and responsibilities preclude dealing with business problems and finding potential solutions.
- There are two strategies to help you work more quickly: asking questions and building relationships. When you ask a question, you can get to know the details of your work faster. When you establish a relationship, you can understand the context of the roles in your organization.
- A good way to learn is to interact with people. Not only can you ask questions and get answers, but you can also see how they find the answers. If it’s a technical issue, you can also look at the coding environment and learn about new ways to intuitively solve it. Even if you want to know how to retrieve data, you will know which table you can get it from, which table to refer to, and coding techniques. Thus, you can answer as many questions as possible just by finding out where to look.
- Again, you should try to meet all the stakeholders you will be working with. If the Data Science team is new, try to meet them. In case, you have a Data Engineer or a Data Analyst working with you, collaborate with them.
If you have any questions or concerns about the Data Scientist roles and responsibilities, please post it to the Data Science Community.
Transition to Data Science through Intellipaat
The ‘Data Scientist’ role was coined a decade back, and today there is a great demand for Data Scientists. For those with analytical thinking, a Data Scientist’s job can be a boon. Consequently, it can be said that as a Data Scientist, you not only need a solid understanding of various data science technologies and tools but also strong business acumen, analytical and strong management skills. Companies around the world are paying huge sums of money to people who can work as Data Scientists and help them discover hidden information in their data. Seems like making a transition to Data Science is the best career move that anyone can take. However, to find the best Data Science job, you need to learn Data Science from a well-known Data Science course provider such as Intellipaat.
For more information on Data Scientist certification courses, please get in touch with us.
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