7 Important Skills needed for an Entry Level Data Scientist

7 Important Skills needed for an Entry Level Data Scientist

Data science is rapidly growing and developing, seemingly with a new application being discovered daily. Data scientists are in high demand from healthcare to finance – making it an attractive industry to join if you possess the necessary aptitude and analytical capabilities.

Data science is rising, yet entering this field isn’t as straightforward as becoming a doctor or lawyer with an entry-level six-figure salary. While data scientists have some advantages over other professions, becoming one requires dedication and hard work – something only some are blessed with.

That’s why we’ve created this guide. Below, you’ll learn about some of the most common entry-level data science jobs and skills along with  providing essential tips for success in a career as a data scientist.

Is It Difficult to Land an Entry-Level Data Science Job?

Acquiring an entry-level data science role shouldn’t be too challenging if you possess the right skillset. Data science is rising, offering plenty of chances for those with little to no experience to break into this field. Completing a data science bootcamp can help in this regard.

7 Entry-Level Data Science Jobs

Are you interested in entering data science and beginning your career? There are plenty of entry-level opportunities available. Here is an overview of seven entry-level positions to help you get your foot in the door.

Data Scientist Intern

A data scientist intern is a new employee learning the nuances of data science by shadowing more experienced data scientists.

Role and Responsibilities:

Data scientists interns usually focus on data cleaning and preparation or statistical analysis. They could assist with developing new algorithms or machine learning models or even create visualizations showing how data is utilized. In some cases, interns may even work on analytics projects tailored toward the company they’re interning at.

To become a data scientist intern, candidates should have experience working with various tools like Excel. Furthermore, they should possess programming languages such as Python, R, or SAS.


On average, a data scientist intern earns an annual salary of $93,452.

Junior Data Scientist

A junior data scientist is new to data science and is learning how to collect, analyze, and present data for other users’ use.

Role and Responsibilities:

A junior data scientist does the same work as a senior one: conducting analysis, reporting findings, and communicating them effectively. However, junior data scientists must gain experience leading projects or working with large datasets or complex machine-learning models.

To be successful as a junior data scientist, you’ll need basic statistics and computer science abilities. Additionally, writing Python code and accessing SQL databases is necessary; depending on the company, you may also require some business analytics expertise.


According to Glassdoor, a junior data scientist earns an average annual salary of $100,265.

Junior Data Engineer

A junior data engineer employed as an intern, part-time, or full-time employee.

Roles and responsibilities:

This job requires in-depth knowledge of data technology, including how it is collected, stored, and analyzed. A junior data engineer typically works on smaller open-source projects with less responsibility than senior engineers.

As a junior data engineer, it is essential to comprehend how data is stored, processed, and visualized. You should possess basic knowledge of SQL and Python programming languages and an in-depth background in mathematics, statistics, and machine learning principles.


A junior data engineer can expect to earn an annual median salary of $88,788.

Junior Data Analyst

Junior data analysts possess the fundamentals of data analysis but are still learning how to apply those skills in a professional setting.

Roles and responsibilities:

A junior data analyst manages and analyzes big data, often working alongside experienced analysts and analytics managers to gain expertise in using various tools for interpretation and interpretation. They may also assist other employees by cleaning up data or prioritizing projects so they can be completed efficiently.

To be hired as a junior data analyst, you must possess strong communication abilities, be comfortable working in a team setting, and lead projects successfully. Furthermore, you should possess basic data analysis principles like statistics and probability and some experience using programming languages relevant to data science like R, Python, SAS/SPSS or SQL.


On average, junior data analysts make around $57,456 annually.

Junior Data Modeler

A junior data modeler is an entry level position responsible for creating and maintaining the database structure of a company.

Roles and responsibilities:

A junior data modeler creates tables, columns and relationships between them; they may also be responsible for other tasks like designing indexes and triggers.

To be hired as a junior data modeler, you should understand relational databases, SQL, and writing queries. Furthermore, you should be capable of working across various platforms, such as Microsoft Excel and SQL.


An entry-level data modeler may make up to $102,851 annually.

Junior Database Administrator

A junior database administrator assists in managing a database-driven website or application, but their responsibilities as an administrator are limited.

Roles and responsibilities:

A junior database administrator assists with the day-to-day running of a database. They create new databases and tables, monitor performance levels, and troubleshoot any issues with their databases.

Junior database administrators must know how to write queries in various programming languages such as SQL or Python and use tools like SQL Management Studio or Toad to manage their databases.


A junior database administrator can earn up to $71,834 annually.

Junior Machine Learning Analyst

A junior machine learning analyst typically has a strong math and computer science foundation, though they are still honing their data analysis skills.

Roles and responsibilities:

A junior machine learning analyst will begin by learning about different types of machine learning, including supervised and unsupervised. They then progress onto more complex topics like neural networks and deep learning. Furthermore, they’ll study algorithms such as k-means clustering or linear regression. Furthermore, a junior analyst must comprehend the significance of data analytics in supporting business decisions.

To be hired as a junior machine learning analyst, you’ll need an in-depth knowledge of statistics and probability. Furthermore, your ability to interpret data and explain its significance must also be demonstrated. Furthermore, knowing linear regression and its limitations is necessary for this position.


A junior machine learning analyst with less than one year of experience can earn up to $103,522 annually.

What skills are needed for an entry-level data scientist?

There are numerous skills required for success in an entry-level data science role. Here are some of the essential ones.

Technical Skills

If you’re seeking a job in data science, technical proficiency is essential. While some data science companies hire people without experience, most will require someone who can program and work with data. Some of the essential technical abilities include:

  1. Writing simple programs in Python, Java or C++ with good knowledge of statistics and probability theory
  2. Excellent command of machine learning techniques such as clustering, regression and classification
  3. A comprehensive understanding of database systems such as MySQL, Postgresql or MongoDB would also be advantageous.
Soft Skills

As a data scientist, you’ll need to be able to communicate your findings to non-technical stakeholders. Soft skills like making presentations and communicating effectively are necessary to do this effectively.

Where Can You Find Entry-Level Data Science Jobs

Here are some great strategies for landing your ideal job:

Job Boards

Online job boards like Monster.com and Indeed.com offer the most obvious starting point when searching for an ideal data science candidate. These sites boast thousands of postings from companies looking to hire those with this background.


Networking is an invaluable way to discover new opportunities in your field and connect with people who can advise or even help you get hired. You can network through friends, family, alum groups or professional associations related to your field.


LinkedIn is an excellent platform to network and discover job openings. Joining groups related to your field will enable posts about open data science positions at other companies to appear in your feed based on the keywords used.

Online Communities

Online communities offer the unique ability to connect with others passionate about data science without ever leaving your house. Plus, numerous online groups are covering almost any topic related to data science you could imagine. You may even find groups specific to certain industries or companies if you’re searching for a job opportunity.

Are you looking for a career in Data Science?

FunctionUp’s Data Science course is an integrated program in AI and data science which will prepare you for exciting career opportunities in data science. Master the field of data science and work with core technology frameworks for analyzing big data. You’ll learn

  • Developmental and programming Frameworks
  • Process massive data
  • Develop expertise in complex data science
  • Implementation using R
  • Statistical processing

FunctionUp’s data science program is exhaustive and a door to take a big leap in mastering data science. The skills and learning by working on multiple real-time projects will simulate and examine your knowledge and will set your way ahead.

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