Data Science Career Paths

In the modern digital age, data is now the currency of business, and data science career paths are proving to be both in-demand and numerous.

More and more, the rise of big data means big opportunities for those possessing specific data science skill sets. It pays to know how to collect, clean, sort, and analyze data in a way that is valuable and provides actionable insights. 

In this post, we’ve collected some standard job titles, their typical requirements, average salary, and the required skillset to hold them. If you’re interested in data science career paths, here’s what to look for.

What is Data Science?

In simple terms, data science is using and preparing data for analysis. It is a data scientist’s job to clean and analyze it to provide digestible and actionable insights to decision-makers and business leaders.

There is a growing need for data scientists and analysts globally to help navigate a digital-first and data-driven global market. Data science is used in just about every corner of the economy – from political forecasts and predicting sports outcomes to forecasting media trends and warning of business slowdowns. Data scientists turn mountains of captured data into neatly packaged, connected dots that detect trends, make predictions, and provide insights into an organization’s goals.

Why pursue a career in Data Science?

The current marketplace combines a high demand for data scientists with a shortage of qualified applicants, making it the perfect opportunity for those interested in entering the field.

Research shows there was a shortage of 250,000 data science professionals in 2020. In addition, 35% of organizations surveyed said they anticipated difficulty finding skilled candidates for data science roles. (1) What’s more, the U.S. Bureau of Labor Statistics reports that the demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026. (2) 

For those with the needed skill sets, companies are paying top dollar, especially for candidates familiar with emerging technologies such as cloud computing, A.I., and machine learning. (3)

Entry-Level Roles

Data Analyst

Average salary: $93,262 USD*

Typical job requirements: A Data Analyst collects and stores data on sales numbers, market research, logistics, linguistics, or other behaviors. They ensure the quality and accuracy of data, then process, design, and present it to help stakeholders make better decisions.

Typical skillset required: Java, Python, SQL, R, Scala

Junior Data Scientist

Average salary: $115,586 USD*

Typical job requirements: Junior Data Scientistsinterpret and manage data and solve 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.

Typical skillset required: Java, Python, SQL, R, Scala 

Data Engineer

Average salary: $116,206 USD*

Typical job requirements: Data Engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. This IT role requires a significant set of technical skills, including a deep knowledge of SQL database design and multiple programming languages.

Typical skillset required: SQL, Python, R, and Scala

Database Administrator

Average salary: $101,097 USD*

Typical job requirements: Database Administrators are responsible for the management and maintenance of company databases. Database Administrators’ duties include maintaining adherence to a data management policy and ensuring that company databases are functional and backed up in the event of memory loss.

Typical skillset required: SQL, PHP, Python, R, C#

Mid-Level Roles

Data Mining Engineer

Average salary: $114,682 USD*

Typical job requirements: A Data Mining Engineer is an advocate for both the database system and its manager. They advise company executives on the best equipment and software to meet the company’s needs and look for opportunities to improve the system and increase its relevance to company goals.

Typical skillset required: Python, Java, R, MapReduce

Data Scientist

Average salary: $118,537 USD* 

Typical job requirements: Data Scientists work closely with business stakeholders. They work to understand their goals and determine how data can be used to achieve those goals. They design data modeling processes and create algorithms and predictive models to analyze data. Combining computer science, modeling, statistics, analytics, and math skills data scientists help organizations make objective, data-driven decisions.

Typical skillset required: Python, SQL, Java, R, Scala

Senior Level Roles

Data Architect

Average salary: $133,823 USD* 

Typical job requirements: Data Architects build and maintain a company’s database by identifying structural and installation solutions. They work with database administrators and analysts to secure easy access to company data. Duties include creating database solutions, evaluating requirements, and preparing design reports.

Typical skillset required: Python, Java, C, C++

Machine Learning Engineer

Average salary: $122,844 USD*

Typical job requirements: Machine Learning Engineers develop self-running AI software. This software automates predictive models for recommended searches, virtual assistants, translation apps, chatbots, and driverless cars. They design machine learning systems, apply algorithms to generate accurate predictions, and resolve data set problems.

Typical skillset required: Python, Java, R, Julia, LISP 

Breaking Into The Field

If you want to break into any of these data science career paths, it’s critical to learn the required programming languages for your target title. 

This can be achieved in several methods – including with university classes or self-teaching – but by far the most time-conscious and cost-effective way is by enrolling in a technical training course that will get you to your goals faster. 

These courses are completed in months, not years, cost a fraction of traditional university tuition, and provide practical training to prepare graduates to jump headfirst into their first position. Short-term, intensive courses teach you up-to-date skills that won’t be obsolete when you graduate. 

Check out all the programming languages and skills Flatiron School will teach you. 

Ready to take the next step? Start with a Free Data Science Lesson, or check out the Data Science Course Syllabus that will set you up for success with the skills to launch you into a fulfilling and lucrative career.

* Salaries cited current as of June 2022 



Top 3 Retail Tech Trends in 2022

Shopping and retail tech in the modern age move at the speed of the internet, and retailers – both big box and boutique – need to evolve to keep up.

The tech that powers personalized shopping experiences, marrying online and in-store data, and cashier-less checkout are only as effective as the engineers behind the scenes.

Trend #1: Digital-First Shopping

While the retail market had already seen a shift away from brick-and-mortar shopping in the early 2010s, the arrival of the COVID-19 pandemic in 2020 cemented the turn towards online shopping. 

Shoppers by and large are no longer walking into physical stores for their goods, instead, they are logging onto their computers with credit cards in hand.

Companies whose digital presence does not present an attractive and easy-to-use platform to users will inevitably suffer in the digital-first modern age and be left in the dust by big-box retailers who offer ease of use. 

Faced with the urgent pressure to digitize, retail tech teams need to modernize their online platforms and will need a technically trained team to keep up.

TIP: Invest in Skilled Engineers

In a recent study, retailers reported software development as the #1 desired technical skill for new hires. Java, software engineering, SQL, Python, JavaScript, and data science also made the list.1  

So, how do retailers build out a technical team to get your digital storefront live and profitable? Sourcing recent graduates from technical training institutions can help ensure that new hires are up to date on the newest software, platforms, and best practices in the online marketplace. 

Over the past 10 years, top retailers such as Amazon, Walmart, Target, and Best Buy have hired our graduates across all disciplines including Software Engineering, Data Science, Cybersecurity, and UX / UI Product Design. 

Big box and clothing retailers in particular source our Software Engineering and Data Science graduates for their skills in Python, Java, JavaScript, and SQL. These languages are used in online interfaces such as cashier-less checkout, virtual storefronts, virtual dressing rooms, and marrying online and offline data to personalize shopping experiences and increase profitability.

See the full skills list taught to our graduates and learn more about hiring our top tech talent

Trend #2: Mobile Commerce

Going hand in hand with the shift to online-first shopping is mobile apps for on-the-go convenience. Customer touch points now feature everything from brand-owned mobile apps to social media platforms, each of which is a chance for retailers’ brand messaging to reinforce customer loyalty. 

But, in a crowded app market with dozens of competitors vying for screen time, how can a retailer increase downloads, user engagement, and – most important of all – mobile conversions? 

TIP: Revamp UX / UI For Seamless Shopping

UX / UI design is a critical success factor in mobile commerce, one that Data Scientists are tackling by connecting data points from multiple systems and gaining actionable one-to-one insights at scale. 

For brand-owned mobile apps, this is often where the most loyal (and profitable) customers aggregate. User experience and user interface can make or break mobile viability, and nothing bottoms out an app’s performance faster than a difficult-to-use interface.

Retailers should utilize UX / UI Product Designers to revamp user interfaces and imbue brand-owned mobile apps with easy-to-use features to ensure a seamless experience that will keep users coming back.

Trend #3: Cybersecurity For The Digital Age

While not a new topic and certainly not unique to retailers, recent cybersecurity trends and high-profile breaches have resulted in several pain points for brands that hold personally identifiable information (PII). 

With the shift towards remote/hybrid working, many retailers are realizing new or increased vulnerabilities including cloud hosting platforms, number of access points, more frequent cyber attacks, and a lack of internal resources struggling to keep up. 

In the digital age where automated attacks can quickly overwhelm retailers, having adept and skilled professionals in place is critical to a company’s continued prosperity and longevity.

TIP: Upskill Cybersecurity Teams

Essential cybersecurity skills for the digital age include SQL, which attackers could use to steal confidential data, compromise data stores, and execute web-based attacks, as well as Python, which helps to scan and analyze malware, and Java, which can be used in penetration (pen) testing.

For retailers to ensure their databases are secure, recruiting cybersecurity professionals with up-to-date and relevant skills or upskilling in-house teams is critical.

Partnering with established training organizations to hire top-level graduates can help retailers build out a team that is up to date with current technology and regulations.

Alternatively, retraining or cross-training existing employees can be a more financially effective option. Utilize technical training organizations to address technical skill gaps on your team and build on existing internal expertise. 

Custom-Tailored Solutions For Retailers

For retailers to keep up in the modern age, skilled technical teams, whether comprised of new hires or upskilled current employees, are critical to long-term viability and profitability.

If your organization is building out a technical team, there are some must-have skills sets to look for:

  • Software Developer / Software Engineer: JavaScript, HTML, Ruby, CSS
  • Full Stack Developer: JavaScript, HTML, CSS, Java, Ruby, Python, SQL
  • Front-End Developer: JavaScript, HTML, CSS
  • Back-End Developer: Java, Ruby, Python, SQL
  • Mobile Developer:  Java, JavaScript
  • Data Scientist: Python, SQL, Java
  • Data Analyst: Java, Python
  • Cybersecurity Risk Specialist / Analyst: SQL, Python, Java
  • Product Designer: UX, UI, ethical and inclusive design
  • UX Designer: UX (user experience), ethical and inclusive design
  • UI Designer: UI (user interface), ethical and inclusive design

But, retailers are busy, and sifting through a mountain of applications takes time. To ease organizations into the digital age with qualified employees, Flatiron School teaches the skills and disciplines retailers’ technical department teams need to keep up.

Software Engineering Data Science Product Design Cybersecurity
Website Development & Management X X
Cashierless Checkout X X
Virtual Storefronts X X
Virtual Dressing Rooms X X
Marrying Online & Offline Data X
Personalization X X X
Brand-Owned Mobile Apps X X
Mobile Social Commerce X
Protect PII X
Inventory Management X X
Sophisticated Pricing Algorithms X X
Increased Shipment / Delivery Speed With Drones, Other Tech X

To see how technical recruiting, upskilling and retaining, or hire-to-train programs offered by Flatiron School can help level up your retail tech team, visit our retail industry page.

Need something special? Talk to our team of retail tech experts about how we can build a curriculum to fit your organization’s needs.