Job hunting can surely be exhausting and stressful; after all, it is a task that comes with many ups and downs. It is even more of a hassle in a field like data science, which is rapidly growing not only in the tech world but also in other industries. The plethora of roles under the data science umbrella also baffles and confuses people into applying for a data science role that may not necessarily resonate aptly with their skill set. Consequently, many people striving to pursue a career in analytics are unsure where to start.
In this blog, we have assembled different data science job roles that aim to help experienced professionals and freshers alike understand the nature of the work that these roles entail.
Data science teams are responsible for solving complex problems with the help of - you guessed it - data. Even though, for the most part, roles under the data science umbrella require data to work with, the necessary skills and tools can vary considerably.
This is an exhaustive list of the top 10 data science roles that are diverse and require a varied skill set. Go through them to understand what role fits best for you, but keep in mind that these data science job titles are not fixed and can vary depending upon the company and industry.
Now without any further ado, let's have a look at the list of data science roles -
The first role that comes to mind whenever we think of data science is of a data scientist. The most general role can also be the jack of all trades. Thereby, to advance in your career as a data scientist, you must understand all the business aspects. You should be able to offer the best solution to business problems by implementing processes, right from collecting and analyzing to visualizing and presenting data.
Here's a data scientist job description that lists all the typical tasks a professional working in this role is expected to perform.
Top companies that have hired data scientists- Deloitte, PwC, Amazon, Microsoft, etc.
The data analyst role sometimes overlaps with the data scientist role due to the similarities that both roles exhibit. A data analyst’s job entails various tasks, including optimizing, visualizing, transforming, and manipulating the data.
The top companies hiring for data analyst roles are - ScienceSoft, SG Analytics, Tableau, Sisense, etc.
The role of a data engineer is crucial for the operation of a data science team. A data engineer's job necessitates developing, testing, and maintaining big data ecosystems optimal for the business and data scientists to run their algorithms.
The top companies hiring for data engineering roles are - Facebook, Airbnb, AT&T, Capital One, etc.
A database administrator's job involves responsibility for directing or performing activities to maintain and secure a thriving database environment. They ensure that the stored data is reliable, error-free, and available. This role also necessitates apt backups and ways to recover data quickly and accurately in the event of failure.
The top companies hiring for database administrator roles are - IBM, TCS, Oracle, AT&T, Bank of America, etc.
Machine learning engineers are highly skilled professionals who work with data scientists and data analysts to perform A/B testing, build data pipelines, and implement machine learning techniques such as classification, clustering, etc., to predict trends and patterns. The ultimate goal of individuals working in this data science role is to eventually create self-running artificial intelligence to automate predictive models.
The top companies hiring for ML engineer roles are - Amazon AWS, Databricks, IBM, etc.
Data engineers and data architects are closely related positions. These data science roles ensure that data scientists and analysts have well-formatted and accessible data to work with. Data architects’ job requires them to formulate the organizational data strategy, including data quality standards, data flow, and security measures.
The top companies hiring for data architect roles are - Northrop Grumman, IBM, Oracle, Abbott, etc.
Primary forms of statistics have always been a part of our civilization which means we can consider this data science role as the historical leader of data and insights. As the name suggests, a statistician is an expert that works with theoretical or applied statistics. It is quite common to combine the expertise of statistics with other fields. In this case, we have organizational data.
Analyzing and interpreting numerical data to derive actionable insights. Performing tests and ensuring the reliability and quality of the data. Assisting in decision-making by refining business strategies. Communicating the results or findings with the stakeholders.
Proficiency with tools such as SPSS, SAS, or Stata. Stronghold over statistical techniques, formulas, calculations, and logic. Ability to leverage algorithms and other technologies to manipulate data. Excellent communication skills to effectively communicate their analysis with other team members.
The top companies hiring for data statistics roles are - IQVIA, Merck, Johnson & Johnson, Apple, Abbott, etc.
Unlike other data science roles, business analysts’ job demands them to work with business operations and information technology (IT) teams to process, analyze, and document business data for procedures, products, or services to extract actionable business insights for business growth.
Understanding all the aspects of business and conducting thorough research and analysis to improve processes and systems. Liaising with different departments and stakeholders to gather information and deliver logical conclusions. Developing innovative solutions to complex business issues in line with operational and strategic improvements. Allocating resources, budgeting, and forecasting.
The top companies hiring for business analyst roles are - Cisco, Accenture, Capital One, IBM, etc.
A data and analytics manager oversees and sets the direction for the entire data science team. They delegate tasks to the team, assign priorities, and design the processes that support a positive outcome.
The top companies hiring for data and analytics manager roles are - Amazon, IBM, Google, Microsoft, etc.
Data science is still evolving, and as it grows, so do the roles that require specific technical expertise. A few examples of such jobs are AI specialists, Deep Learning specialists, NLP specialists, etc. Such data science roles shrink the perimeter of the general data science workload and enable the professional to focus on one specific technology.
After going through the list of these diverse data science positions, you must have decided to push your data science career. But, even after determining the role you want to grow in, it is not an easy task to land the right data science job.
What’s the solution?
The solution is Turing.com. It is an AI-driven deep jobs platform that enables you to apply for remote jobs at US-based companies from the comfort of your home. So, if you’re looking to get full-time, long-term remote data science jobs with better compensation and career growth, apply for Turing jobs today!
Anupriya is a content writer well-versed in researching and writing on an array of topics. She works closely with businesses and helps them get rapid and organic growth through compelling digital marketing content. When not working, you can find her reading or sketching.
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