A data analyst works in one of the fastest-growing fields, data science. The need for analysts is growing, as more value is placed on the skill set, which is to help understand current metrics and predict future outcomes using data modeling and techniques. But is there a demand for part-time analysts?
A data analyst can work part-time only due to a shortage of data analysts in the workforce. Especially if you are experienced, you will be in great demand. As a beginner, if hired part-time in multiple companies, you will quickly gain the experience to move ahead in the data science field.
If part-time work as a data analyst has ever appealed to you, continue reading and discover what qualifications and approach you need to obtain a part-time job in this professional role. Also, read on to learn what positioning techniques will help an analyst move ahead in the field.
Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!
Table of Contents
Data Analysis as a Part Time Career
The career of a data analyst falls within the data science domain, which contains everything pertaining to data, specifically, computing power and velocity combined with data gathering, storage, modeling, and predicting. The final goal of data science is to resolve organizational problems and plan for the future.
The data analyst performs a very important portion of that work by providing analytics support that utilizes critical thinking skills to organize data into usable information. Consequently, major job skills needed to be considered an expert data analyst are to understand the business environment in the industry you are working in, be able to collaborate with cross-functional teams, be able to dispense huge amounts of data in a logical and effective manner to resolve a company issue, and to project data into the future so that planning decisions can be made.
An analyst must be able to report and disseminate information in an informal scrum meeting or a board room full of executives, both internal or external, to the company. Therefore the characteristics that create a brilliant professional are varied and hard to come by. If you are an experienced and talented data analyst, you will have the leverage to negotiate a part-time position, as desired.
Data Analyst Defined
Specifically, a data analyst is a stepping stone to becoming a data scientist. Your knowledge is used to determine resolutions to problems using computer systems, identify and report information behind the numbers, and discover trends and new opportunities.
In order to accomplish the workflow, an analyst must be able to shift from strategy to operations and back very quickly. After identifying the need, the analyst will:
- Gather data.
- Clean and place in a data warehouse.
- Aggregate data.
- Perform tests, run models, provide experiments.
- Report and present metrics, risks, insights, predictions, and other discoveries that pertain to the issues.
In a team, the computer programmer or statistician may lend a hand to data analysts with some of the responsibilities. Or the data scientist may take over and create new models and tests, refine and massage the date further. Teams use the abilities of its members and each company has different expectations for collaboration. Teamwork lends itself well to a part-time job.
Data Analyst Qualifications
The analyst must always keep the big picture in mind but be able to jump into the fray and perform statistical concepts or code as needed. Experience in programs and applications will factor into the hiring process. Because the demand for data science professionals is so high today, with your knowledge and experience, you will have the power to influence hiring decisions to land a part-time position in this domain.
- Acquire certification in Microsoft Excel.
- Become proficient in industry-standard statistical programming languages.
- R is a time tested, open-source language with a huge following.
- Python is well known, easy to learn, open-source, and is a scripted language.
- C++ is a common, general-purpose language.
- Java is an object-oriented programming language.
- MATLAB is an abbreviation for Matrix Laboratory and is a numerical computing environment.
- Learn a query language to pull and examine massive amounts of data so that analytics can be performed.
- Structured Query Language (SQL) has been in existence since the 1970s and is tried and true. As a beginner, learn the basics of SQL in no time by watching a free training video on YouTube.
- Gain a strong understanding of data warehousing and data storage options.
- Data visualization software experience.
- Tableau is used to gather data and use it to paint a picture using charts, visualize market trends, and many other techniques to present your information. It’s an extremely powerful tool that is very often used in business.
- Take a class in math and statistics to obtain a high level of understanding.
- Continually be aware of changing trends and technologies.
The preceding job qualifications are not mandatory. However, having them on your resume sets you apart from the rest by being able to wear multiple hats, understand strategy, as well as the technical pieces. Accordingly, in becoming an analyst, even if you are used to working in a different domain, that experience is transferable. Consequently, be sure to showcase previous job skills.
Research an industry that you want to break into or are already involved in another capacity. Most industries see the value of data analysis employees, and to a great extent, businesses are already hiring and are reaping the rewards, including the following:
- Enterprise Management
- Retail and eCommerce
- Finance
- Information Systems
- Insurance
- Manufacturing
- Professional Services
- Scientific Services
- Technical Services
- Utilities
For the basics of becoming a data analyst, there are massive amounts of reading material that deliver information specific to your industry. The book entitled “Data Analytics For Beginners” on Amazon provides a wide range overview.
Position Yourself as a Great Candidate for Data Analyst Roles
On the Job Training
- Intern or work as a data analyst in the industry or domain that you are interested in.
- Create a portfolio of projects.
- Job shadow or schedule an informational interview.
Networking
- Expand your business network.
- Volunteer as an analyst for a non-profit.
Certification
- Get certified in a statistical programming language.
- Obtain a data analyst certification. For example, the Cloudera Certified Data Analyst is offered online.
Read
- Devour industry-specific books. If you are in the retail arena, “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die” is packed with great real-world examples and tips specific to selling products.
Soft Skills
- Develop critical thinking skills.
- Maintain a common-sense attitude.
- Develop impactful presentation skills.
Education
Earn a Bachelor of Science or Bachelor of Arts degree in any of these areas:
- Data analytics and policy
- Data analytics and engineering
- Business analytics
- Business intelligence and data analytics.
- Statistics
- Computer programming
- Mathematics
To carry out all of the job duties of a data analyst, unique performance demands are required. Once again, being able to quantify these on a resume or via a reference will help your case for part-time employment:
- Absolute accuracy
- Attention to detail
- Answer to multiple department heads
- Report to a variety of areas internally and possibly externally
- Expert communication
- Influential and clear presentation
- Ability to meet deadlines
- Create understandable output, being perceptive to your audience
- Assume a heavy workload
- Continually learn and develop as new tools and processes are put in place
Job Hunt
When looking for a part-time position, if the company is small with low data volume, you may be working on every aspect of the project from data gathering to resolving the problem. With a bigger company, there are more members on the team and you may be hired to do a specific piece of the project. Ask questions during the interview and decide what works best for you.
If you are new to data analysis, it may be advantageous to see the project from beginning to end as an excellent learning experience. Also, as an inexperienced worker, choose an industry with longevity. The list below includes industries that are known for needing data analysts for the long haul.
- Finance
- Retail and eCommerce
- Information Systems
- Manufacturing
- Scientific Services
- Technical Services
- Telecommunications
- Utilities
Recruiting services and online resources are excellent venues to find part-time work. Keep networking in person and online, and be clear about your desire for part-time work. Be open to job sharing with another analyst. Although part-time jobs are hard to find when data analysts are in great demand, you have the advantage, and if you’re flexible, you will be able to negotiate a deal that works for you.
Author’s Recommendations: Top Data Science Resources To Consider
Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.
- DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
- IBM Data Science Professional Certificate: If you are looking for a data science credential that has strong industry recognition but does not involve too heavy of an effort: Click Here To Enroll Into The IBM Data Science Professional Certificate Program Today! (To learn more: Check out my full review of this certificate program here)
- MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
- Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.
Conclusion
Awareness that data analysts are in short supply enables you to leverage your experience to create a part-time space in any industry. If you are just starting out, it’s well worth your time to create a solid background, including education, technical abilities, and soft skills, in order to define your own part-time work schedule.
In addition, this article maps out a career path for advancement if you choose to evolve into a data scientist. Nevertheless, whichever path you decide to take, data analysis is a smart choice due to the lucrative salaries and the need for analysts now and in the years to come.
BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.
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