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Data Science Careers That Might Interest You


Data Analytics

Data Science Careers That Might Interest You

Data science is a data-driven field of study that can lead to many different types of careers. These experts are in high demand, and data science salaries are growing rapidly. There are plenty of choices for everyone. In this article, you will learn about some data sciences careers that might interest you!

Data Engineer

Data engineering is a high-demand job right now. Scientists need engineers to help them mine through the data and find key insights that will drive decisions for a business.

Data engineer jobs can be a great opportunity if you already have experience with coding languages like Python, C++, or Java because it’s going to give you an edge in this industry. Also, since businesses are looking for people who know how to code but also understand how algorithms work behind the scenes, there tend to be more opportunities available too!

If you are not familiar with these programs but are interested, there are places where you can educate yourself. You can even become a master of data science online with the help of various courses. This is a great way to expand your horizons and career opportunities.

In terms of salary expectations, most data engineering careers pay around 100k/year depending on where you live and your level of expertise. This may sound high compared to other industries out there right now (especially when we look at what software engineers are being paid), but data engineering is a crucial job for businesses right now, so it’s not going to go away anytime soon.

Machine Learning Engineer

Another field of data science that is connected to engineering is machine learning. As data scientists, machine learning engineers are responsible for developing data-driven applications through algorithms that can learn from data to improve its performance over time.

This includes the creation of models and tools that allow computers to use data instead of being explicitly programmed against it which has helped propel new areas in technology such as autonomous vehicles. It is possible with machine learning engineer career role but ultimately companies will need both roles filled by their employees depending on what they're trying to develop or build.

A data scientist would be able to work more towards building a model while a machine Learning Engineer will focus more on how an algorithm works and making sure there aren't any bugs within the code itself.

An example we can use here could be working at Google Maps where data scientists are using machine learning to predict traffic patterns and how long it will take for a person to get from one place to another. A data scientist would focus on the results of this data which might be used by businesses or drivers themselves while a machine learning engineer is more concerned with what's happening under the hood so that they can create better models in the future based on previous experiences.

Applications Architect

Application architects are data scientists who oversee data flow and communication between software components. They ensure data flows happen in an organized way, data is integrated properly, and communication happens to make sure the data gets where it needs to go.

Key Skills to Include:

You can become an application architect by earning a data science degree and obtaining experience in data engineering.

Data Architect

Another architectural job choice in data science is a data architect. This is a more senior role that requires experience in designing systems from the ground up and being familiar with all aspects of building cloud-based apps, including infrastructure provisioning & management, containerization, storage orchestration, etc. In general, they are looking for someone who understands how to build cloud-based services at scale on AWS or any other cloud provider(s).

Data architects have strong analytical skills since it’s their job to identify system bottlenecks and come up with an optimal solution that scales well while maintaining a low cost per query/transaction. They also need coding abilities so they can write scripts using languages such as Python / Scala / GoLang (for Data Science) or Java (to interface with relational databases).

It usually pays around $110,000 in the USA which is why data architects are in high demand.

Infrastructure Architect

An infrastructure architects' job is to provide data scientists with the data they need to create data products. They might work in a data-driven product where their job is to design, plan and maintain the systems which store, process, and serve data.

Job Responsibilities

Data Scientists rely on infrastructure architects for all kinds of things when creating data products including storage space, cloud computing services like AWS or Azure, databases (SQL or NoSQL), version control tools such as Github/Bitbucket, etc., network access permissions and so much more! It's no easy task being an infrastructure architect.

It requires a lot of attention to detail plus dedication & patience which means it is not your typical entry-level job but perfect if you're looking for something challenging yet fun!

Business Intelligence Developer

Your responsibilities at this job would be to create data-driven solutions for business needs. You'll have to write queries and reports, automate data collection, perform data analysis with BI tools, implement data visualization dashboards, build KPIs metrics and provide users with the most useful data possible.

If you are interested in this career choice then it might be time for you to get certified. It's not usual to hire people for this position without data scientist certification. Additionally, you can take data science courses to complement your data analytics knowledge and skillset.

Statistician

Statisticians in data sciences are data analysts who are responsible for data collection, data organization, and data analysis. Data scientists working in this career field will need to be able to transform large datasets into actionable insights that can help businesses make better decisions about their products or services. This is an important job because having accurate information available on any given product or service enables companies to more successfully market what they offer.

Statisticians work with data mining tools and use statistical software programs like R and SPSS. Many statisticians also become business consultants/analysts when they finish school. If you’re ready to advance in your career as a statistician, think about getting a master's in applied statistics online.

Data sciences careers are thriving and you should take advantage of the many high-paying opportunities out there. Whether it's in engineering or architecture, they are good choices that can help you towards a nice career path. If you're not interested in either of those you can still become a business intelligence developer or a statistician. There are a lot of choices and are just waiting for you to finish a course and start your job!


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