Organizations hire data scientists at various levels, including junior, mid-level, and senior-level positions. Just like any other career, there is a certain path to be followed. Interns aside, the “junior data scientist” is one of the main entry-level positions in this career.
However, people still question about what a junior data scientist do exactly, and the answer isn’t simple since various corporation have different expectations from employees at an entry-level.
In this article, we’ll dive into the world of data sciences and understand what it’s like to be a junior data scientist in a world where data plays a major role in decision making.
Let’s get started.
What Does a Junior Data Scientist Do – Typical Roles in Organizations
In recent years, as big data became a commodity, there has been a dire need for data science to make crucial decisions regarding marketing, management, finance, and human resource. This need has expanded the demand for data scientists exponentially. Regardless of the scale and size of the business, it has become essential to have a team of data scientists to interpret the incoming data.
Junior data scientists are responsible for interpreting and managing data and solving complex problems with the help of various data software. A typical job description for a junior data scientist would include things such as having an extreme passion for data science and data analysis, being able to conduct data mining, and working in teams.
However, the role of a junior data scientist may vary with the scale and size of the organization. There is a set of pros and cons to working in a small-scale organization or a large-scale organization.
If a junior data scientist decides to work in a small-scale organization, they will have the privilege of acquiring the skills required to becoming a mid-level or senior data scientist through on-job experiences. However, the workload may be a bit overwhelming to some.
If a junior data scientist decides to work in a large-scale organization, they will have the chance of being mentored by mid-level or senior data scientists which will help them in developing the necessary skills they need to progress in their career. However, the process of being promoted to the next level can be very slow.
Let’s take a deeper look:
In small-scale organizations, the junior data scientist job title may also take up the responsibility of being a mentor to the interns and visualizing the collected data to the managers of different departments. Furthermore, the junior data scientist may explain the data to the stakeholders to aid them in decision-making.
In a small-scale organization, the workforce is smaller as compared to a large-scale organization. This leads to junior data scientists taking up roles similar to mid-level or senior data scientists.
In large-scale organizations, the role of a junior data scientist is restricted to extracting data and data analysis. The role of mentoring recruits, data visualization, and creating non-technical reports regarding the data extracted falls onto the shoulders of mid-level and senior data scientists. Furthermore, it is the responsibility of the mid-level or the senior data scientist to explain the data to the managers.
In larger companies, the work is divided among other employees such as mid-level and senior data scientists. The division of labor decreases the workload and leads to efficiency.
What Does a Junior Data Scientist Do – Duties and Tasks
The role of a junior data scientist varies from organization to organization. This can make it even more confusing to understand the role of a data scientist. The best way to answer this question is to consider the typical duties and tasks junior data scientists are responsible for and carry out on a daily basis.
Duties of a Junior Data Scientist
Duties are a list of responsibilities that an individual has to fulfill to meet the aim of their job. Junior data scientists have a list of duties that they have to abide by to make sure they work efficiently and can perform under the given deadline.
These duties are designed to make sure that the junior data scientist can fulfill their given role in the organization by simply doing the assigned duties.
The duties of a junior data scientist are the following:
- Mining and analyzing data from the company’s databases to provide managers with meaningful information through which they can design and implement strategies that will optimize the company’s profits and revenue.
- Creating custom data algorithms to extract data as much as possible and also to understand the extracted data better. A better understanding of the data will help managers in making effective decisions.
- Collaborate with managers from different departments in implementing strategies and monitoring the outcome of the strategies: is the outcome similar to the prediction or not.
- Design tools and software to track projects over a specific period and analyze the result of a given project.
- Searching for new, cutting-edge tools and software to increase the accuracy and the effectiveness of the data extracted from the company’s databases.
- To organize and use predictive modeling to predict revenue generation, profit, customer growth, and sales. The perfection of such predictions can help the company in predicting a more accurate outcome to business strategies which will help managers in decision making.
Keep in mind that the aforementioned duties may be a bit different in your organization.
Typical Tasks Allotted to a Junior Data Scientist
To understand what does a junior data scientist does exactly, we need to look at the daily tasks they conduct to fulfill the duties assigned to them.
These tasks are more or less related to data mining and data analysis.
The list of task a junior data scientist has to perform on daily basis include:
- Before extracting the data from the company’s databases, the junior data scientist should be aware of the purpose of why are they extracting the data in the first place. The purpose could be to understand what marketing campaigns have worked previously through extracting data regarding sales done in a specific period.
- A junior data scientist is typically responsible for acquiring data through software and algorithms such as DATAQ.
- They are also typically responsible for cleaning and processing the data through filtering the useful data from the useless data.
- They are often expected to integrate and store the data collected from the company’s database in the server.
- Initial investigation and data analysis as a way to interpret the data collected from the company’s database is usually the job of a junior data scientist.
- Junior data scientists use more than one algorithm or model to understand the trend displayed by the data.
- For further analysis, junior data scientists use tools such as machine learning, artificial intelligence, natural language processing, and statistical modeling to understand the data better.
- Accuracy is the top priority of any junior data scientist. To make sure they can deliver that accuracy in the results, the results are measured and are constantly improved upon.
- The results are presented to the mid-level or senior data scientists.
- Data is adjusted and further improved upon according to the criticism given by the mid-level or senior data scientists.
The processes listed above are repeated each time a new set of problems arises.
Difference of Duties and Tasks Based on Organization Size
In a large-scale organization, the duties and tasks are divided among other professionals such as data analysts, data engineers, business intelligence specialists, and data architects. This division creates specialization of labor which increases productivity and efficiency. In a large-scale organization, the task and duties of a junior data scientist revolve around extracting data from the company’s databases.
However, in a small-scale organization/startups, the junior data scientist has to fit into the role of a data analyst, data engineer, business intelligence specialist, and data architect. Due to the lack of labor present in the small-scale organization, the junior data scientist has no other option but to take up these roles and responsibilities.
The duties and tasks allotted to the junior data scientist vary from organization to organization. However, what does not change is the nature of these duties and tasks.
Skills and Abilities Required to Become a Junior Data Scientist
Junior data scientist are required to have immense knowledge regarding computer science, data science and math.
Furthermore, junior data scientists are also required to have skills such as programming, machine learning, data wrangling, statistics, data visualization, and data intution. Critical thinking and being able to work in data science teams are some of the few things a junior data scientist should be able to do.
Required Skills Needed to be a Junior Data Scientist
The prerequisite skills include:
Programming is an essential skill that every junior data scientist should have.
One should learn statistical programming languages such as R, Python and data querying languages such as SQL.
Junior data scientists use programming to organize unstructured large data sets and analyze the given data further. One can learn programming through signing up for a code camp or registering yourself for an online course.
Machine learning is used to analyze huge blocks of data with minimal human interaction.
A junior data scientist should master the art of machine learning as a way to analyse data efficiently. Machine learning can be learned through online courses offered by various universities.
A sub-set of data management, data wrangling is refers to gathering, selecting, and transforming raw data to answer an analytical question.
This skill helps junior data scientists filter out the important data from the useless one. Some examples of tools that are used for data wrangling include Microsoft Excel and OpenRefine.
An excellent understanding of statistics and data analytics is vital for a junior data scientist. Specifically, familiarity with concepts such as statistical tests, distribution, exploratory data analysis, regression, and maximum likelihood estimators is crucial.
It is also important for a junior data scientist to know when to use a certain technique or not.
Visualization and communication of data is very important as it plays a huge role in decision making in data driven organizations.
Therefore, it is important that junior data scientists equip themselves with the skill of visualizing data through tools such as matplotlib, ggplot, and ds.js. Communication of data is as important as visualizing it, as communication helps manager to understand the data presented.
One of the most popular tools for data visualization and dashboarding is Tableau. A junior data scientist shouldn’t be just aware of these skills but should also know the logic behind data visualization and communication.
A junior data scientist should have the intuitive understanding of when to apply what concept to get the required outcome – a skill known as data intuition.
It is important for the junior data scientist to retain previously taught knowledge and skills, so they can apply their knowledge onto real life situations as quickly as possible.
Required Abilities Needed to be a Junior Data Scientist
Critcal thinking, being able to work with team members , quick thinking, adaptability, data storytelling, and problem-solving skills are the most things that a junior data scientist should be able to do. These abilities can help junior data scientists to learn the skills stated above at a shorter period of time.
Furthermore, these soft skills can also help junior data scientists to adapt to the work place environment.
The skills and abilities stated above can help the junior data scientist to accomplish any given task efficiently and productively. Through mastering these skills and abilities, a junior data scientist can move up the ranks of the corporate ladder.
How to Become a Junior Data Scientist
In recent years, organizations have began to realize the crucial role data plays in effective decision making.
According to the Bureau of Labor Statistics, data science is a new upcoming field with a growth potential of 28% annually and is projected to grow by 31% in the next ten years.
Data from Glassdoor suggests that the average base salary for full-time data scientists $81,222/year. In some organizations, the average junior data scientist salary can go up to $127,000. It really depends on the years of experience you have.
These professionals typically need a bachelor’s degree in I.T, computer science, math, physics or another related field. Most organization require at least 1 year of work experience in the related field. In a small- scale organization, individuals with less than 1 year of experience can also apply.
Before applying for a junior data science position, its important to make sure your resume stands out from the rest of the applicants.
Emphasize on your skillsets and soft skills in your resume as that may help you in gaining the attention of the recuiters. You can ask a mid-level or senior data scientist to review your resume before you submit it to the recruiters.
As you may wait for recuiters to reply, you can gain further knowledge through taking online courses on data science. These courses can help you in understanding the field of data science and will equip you with additional skill that can be beneficial at your first day as a junior data scientist.
Becoming a Great Junior Data Scientist
If you’re qualified and ready to be a junior data scientist, the next logical step is to understand the role a junior data scientist plays in an organization. Through understanding the role of junior data scientist, you will able to mentally prepare yourself for the role. However, the role of a junior data scientist depends on the organization you have decided to work with.
If it’s a large-scale organization, your role as a junior data scientist will be restricted to conducting data mining and data analysis. However, if it’s a small-scale organization, your role as a junior data scientist will revolve around doing tasks that a mid-level or senior data scientist would do.
Becoming a great junior data scientist is about perfecting your skill in data mining and data analysis. The more skillful you are as a junior data scientist, the better you are in completing your duties and tasks efficiently. You can learn to be a better junior data scientist by exposing yourself to new experiences and situations.