Are you looking for a career in data science?

Data is the building block of futuristic technologies like machine learning and artificial intelligence, since they are dependent on data.

Data science is the methodology to collect, analyze, and process bulky sets of unstructured and structured data. Innumerable people have joined the race to become a Data Scientist, due to its rewarding and lucrative nature.

However, the data science career path is not for everyone. You need to possess high analytical and mathematical skills to become a successful data scientist.

You do not need any specific technical degree to build a career in the data science domain. All you require is the right skill set, with experience or certifications to kickstart your data science career.

This blog contains all the essential information about different jobs in data science industry, here is our blog summary:

  • Get all the essential details related to Data Science careers to choose your path
  • Check out the average Data Science Salary based on the profile title
  • Take a glance at the Data Science Career Trajectory to defile the milestones
  • Know the difference between Data Scientists and Data Analysts
  • Follow the steps given to apply and get your desired data science job

What is a Data Scientist?

Data scientists are professionals with analytical, mathematical, and programming skills. They analyze large sets of data and implement the results to achieve organizational goals.

Data scientists work as an active medium between business and IT operations. They focus on improving products or services to get maximum business opportunities within an enterprise.

To start your data science career, you need technical skills like data analysis, statistics, Python, Hadoop, etc.

Data Scientist Job Description

The data scientist job description will play a vital role in the shortlisting process, since it provides the key skills/words that should be present in your resume. You can add these industry-specific keywords to your resume to grab your recruiter’s undivided attention.

The job description gives an overview of the prerequisities for any desired role. You should frame your data science resume based on the job description in order to boost your chances of getting shortlisted.

Popular Data Science Career Paths

Data Science is a vast field that requires potential professionals to possess expertise in capturing & analyzing large data. So if this is the career path you choose, make sure that you are familiar with the required skills. The good news is that there are numerous career options for people with a background in Data Science.

Here, we have cherry-picked some popular data science job profiles that will keep growing with the technological advancements across the globe. You can pursue any of these data science careers to become a successful data science professional:

Machine Learning Scientist

A Machine Learning Scientist researches fresh data algorithms and approaches to use in adaptive systems such as deep learning, supervised, and unsupervised techniques. Generally, these professionals are also reffered to as Research Engineer or Research Scientist apart from Machine Learning Scientist.

Machine Learning Engineer

Machine Learning Engineers are responsible for developing data funnels to deliver modern software solutions within an enterprise. These professionals are required to possess strong programming and statistical skills along with deep software engineering knowledge.

As a machine learning engineer, you will also have to run experiments and tests for monitoring the smooth performance of the entire machine learning system.

Enterprise Architect

An Enterprise Architect builds, transforms, and aligns strategies or an organization with the suitable technology to get desired results. Hence, these professionals must have a thorough understanding of businesses and the technologies associated with it. As an Enterprise Architect, you will have to design the entire system architecture of a company.

Application Architect

The main objective of an Application Architect is to track the behavior of applications used in an enterprise to ensure smooth interaction between employees and external clients.

As an Application Architect, you will also need to design the application architecture including the user interface.

Infrastructure Architect

Infrastructure Architects ensure the optimal working of all the business systems being used in a company. These professionals help in the development of system requirements and new technologies as per the business requirements.

Cloud Architect has similar roles & responsibilities to that of an Infrastructure Architect, who also manages the company’s cloud computing strategies.

Data Architect

The main function of a Data Architect is to build performance-focused data solutions and analytics applications within a company. Apart from developing new databases, Data Architects also work for improving the functionality and performance of existing systems.

As a data architect, you will be responsible for providing database access to relevant analysts and administrators.

Business Intelligence Developer

A Business Intelligence Developer designs and develops effective business strategies to help users in procuring desired information easily, as part of making better business decisions.

To be a Business Intelligence Developer, you will have to be extremely tech-savvy, as this profile is responsible for building business intelligence tools and BI analytic applications.

Data Engineer

Data Engineers process already stored data in an organization. These professionals also work for developing and managing data pipelines to create an interconnected and robust data ecosystem.

The primary function of Data Engineers is to ensure the availability of required data to data scientists.

Data Analyst

A Data Analyst transforms and manipulates bulky datasets to analyze them as per the company’s requirements. Data analysts also perform web analytics tracking and A/B testing analysis in many organizations.

As a Data Analyst, you need to make data reports for the management team to aid the decision-making process.

Statistician

Statisticians are responsible for collecting, analyzing, and interpreting data for a company. These operations help in improvising the decision-making process of the business.

Apart from that, other responsibilities of a statistician include, designing the data collection process, maintaining effective communication with the stakeholders, and enhancing organizational strategies.

Data Science Average Salary

The salary range for a data science professional varies based on different factors including profile title, education, certifications, and company location.

To give you an idea about the data science average salary, we have done research on a popular career platform named Glassdoor. You can check out the average data science salaries in the United States according to profile titles.

Profile Title Average Annual Salary
Data Scientists USD 1,17,212
Machine Learning Scientist USD 1,37,053
Machine Learning Engineer USD 1,31,001
Enterprise Architect USD 1,50,782
Application Architect USD 1,29,000
Infrastructure Architect USD 1,27,676
Data Architect USD 1,18,868
Business Intelligence Developer USD 92,013
Data Engineer USD 1,12,493
Data Analyst USD 69,517
Statistician USD 88,989

Data Science Career Trajectory: From Data Analysts to Data Scientists

data-scientist-career-trajectory

Getting a data scientist job might look like a tough task as you need to have all the essential skills along with previous work experiences as a data analyst or similar roles.

The above-given image showcases the path you need to travel for becoming a data scientist. There are numerous roles associated with data science, you can take your pick depending upon your areas of interest and skill set.

You need to have a strong knowledge in Statistics, Artificial Intelligence, Big Data Analytics, and Data Management to become a Data Scientist.

Gaining expertise in Python, Machine Learning, and Relational Databases will help you get the data system developer profile title.

Data Analysts Vs. Data Scientists

The education, skills, and responsibilities of entry level data scientists and data analysts seem to overlap and confuse many individuals. Both of these profiles require programming capabilities along with statistical knowledge.

Still, both of these profiles are different from each other. Let us see how:

What Does a Data Scientist do?

Data scientists work around delivering answers to business improvement questions while working with data sets. These professionals help the development team to build new and effective product features based on the results obtained by the collated data.

Data scientists spend most of their time cleaning data to use it in machine learning algorithms and business models. An example of the same would be Netflix, where you always get a section of recommended shows and movies. Behind the curtains, this section is a result of data science and machine learning algorithms.

Data Science Skills

The core skills for entry level data scientists are:

  • Data Modeling
  • Big Data
  • Machine Learning
  • Data Visualization
  • Statistics
  • Programming
  • Teamwork

What Does a Data Analyst do?

Little different from data scientists, a data analyst focuses only on getting answers about the available data. These professionals are not concerned with leveraging data to improve the decision-making process for a business.

In simple words, a data analyst works with existing data!

The core functionalities of a data analyst are to design systems, analyze the available data, and run A/B testing for the product. Data analysts are required to be proficient in data warehousing, data storing and utilizing technical tools like Tableau.

Data Analyst Skills

The major skills you must have as a data analyst are:

  • Domain Knowledge
  • A/B Testing
  • Data Visualization
  • Microsoft Excel
  • SQL
  • Reporting
  • Programming

How to Get Data Scientist Jobs

Data Scientists are highly intellectual professionals and perform a pivotal role in the growth of a company. A technical educational degree and data science certifications will render you eligible to apply for data scientist jobs.

Still, you will need a professionally framed data science resume along with a finely crafted data science cover letter to move a step ahead for getting a data science job. You can follow the below-given steps to jump start your data science career:

  • Select your desired data science career profile.
  • Make a master folder and all the soft copies of all the essential documents
  • Read the job description and pick industry-specific keywords from it
  • Outline your resume in reverse chronological format for a better impression
  • Add all of your essential details in bullet points starting with a power verb
  • Add profile centric skills, keywords, and important metrics to make your resume technically strong
  • Highlight important keywords to grab the recruiter’s attention
  • Craft a data science cover letter for your job application
  • Apply and send your application form with your data science resume, and cover letter

A data science resume will be your backbone during recruitment process. Hence, you need to frame it appropriately to impress your recruiter. You can leverage Hiration’s expert assistance for this task.

Hiration has built an AI-powered Online Resume Builder to help you create a highly impactful data science resume. It features a marvelous auto-suggest functionality that will assist you during the entire resume-building process.

Data Science Career Guidance at Hiration

Hiration is dedicated to the sole goal of providing guidance to professionals in building their career. We are here to assist you during your entire recruitment process. You can also leverage Hiration’s Interview Preparation facility to take down your interview round without any hurdle.

Here are some of the major offerings you will see at Hiration:

Key Points

Data scientists have become a strong pillar of every successful organization these days and there is a great demand for data scientists even in growing companies. You can move ahead on the data science career path with the right set of data science degrees, certifications, skills, and experience.

You can see all the profiles major in data science in this blog. Moreover, we have also tried to elaborate on the difference between these data science career profiles. To get more information on data science, you can check out the following blogs:

If you come across any hurdle in the application process of your desired data science job, you can always contact us at team@hiration.com. We will be highly obliged to help you in getting your desired data science jobs.