see, https://www.springboard.com/blog/data-science-career-paths-different-roles-industry/
In general,

There are data scientists who fine-tune the statistical and mathematical models that are applied onto data. When somebody is applying their theoretical knowledge of statistics and algorithms to find the best way to solve a data science problem, they are filling the role of data scientist. When somebody builds a model to predict the number of credit card defaults in the next month, they are wearing the data scientist hat.

A data scientist will be able to take a business problem and translate it to a data question, create predictive models to answer the question and storytell about the findings.

Statisticians that focus on implementing statistical approaches to data, and data managers who focus on running data science teams tend to fall in the data scientist role.

Data scientists are the bridge between the programming and implementation of data science, the theory of data science, and the business implications of data.

Skills You’ll Need: Knowledge of algorithms, statistics, mathematics, and broad knowledge of programming languages such as R and Python. Broad knowledge of how to structure a data problem, from framing the right questions to ask, to communicating the results effectively.

Salaries: Data scientists need to have a broad set of skills that covers the theory, implementation and communication of data science. They also tend to be the highest compensated group with an average salary above $115,000 USD.

Sample Job Posting: This data scientist posting at Apple is looking for scientists who are both passionate about creating data driven systems and which have experience in statistical programming. You can truly see the versatility of the data scientist role in this description! The data scientist in question will play an important role in providing fast searches for Spotlight on Safari.

Typical Majors: Mathematics, economics, computer science, physics

Open Job Positions on Indeed.com: ~22,000 (18% over $115,000 salary estimate)

Industries that are Hiring Data Engineers: Software, medicine, audio companies

Top Hiring Locations in the United States: New York City, San Francisco, Seattle

Things You’ll Catch Them Saying: “My classifier gave me 93% accuracy on the first try! [Pause] Something must be wrong with the data …”

There are data engineers, who rely mostly on their software engineering experience to handle large amounts of data at scale. These are versatile generalists who use computer science to help process large datasets. They typically focus on coding, cleaning up data sets, and implementing requests that come from data scientists. They typically know a broad variety of programming languages, from Python to Java. When somebody takes the predictive model from the data scientist and implements it in code, they are typically playing the role of a data engineer.

Data architects that focus on structuring the technology that manages data models and database administrators who focus on managing data storage solutions tend to be part of the category of data engineers.

Skills You’ll Need: A deep knowledge of data storage and warehousing solutions (SQL and NoSQL – based flavors), and programming frameworks such as Hadoop and Spark that can help you source data and process it.

Salaries: Data engineers often focus on the implementation of data science by making sure code is clean, and technical systems are well-suited to the amount of data passing back and forth for analysis. They tend to be middle of the pack when it comes to compensation, with an average salary around $100,000 USD.

Sample Job Posting: Shopify is a Canadian startup that allows you to open an e-commerce store without having to build anything in code. Their posting for a data engineer requires you to have extensive software development experience along with extensive database experience. They are looking for people who are proficient in Python and Scala. They need “passionate software and operations engineers who are excited about data.”

Typical Majors: Computer science, engineering.

Open Job Positions on Indeed.com: ~98,000 (17% over $115,000 salary estimate)

Industries that are Hiring Data Engineers: Software, aerospace, information technology

Top Hiring Locations in the United States: San Francisco, New York City, Seattle

Things You’ll Catch Them Saying: “My data pipeline would be perfect if it wasn’t for the people using it.”

there are data analysts who look through the data and provide reports and visualizations to explain what insights the data is hiding. When somebody helps people from across the company understand specific queries with charts, they are filling the data analyst role.

Business analysts are a subset of data analysts that are more concerned with the business implications of the data and the actions that should result. Should the company invest more in project X or project Y? Business analysts will leverage the work of data science teams to communicate an answer.

Skills You’ll Need: Data analysts will need a solid grasp of data manipulation (using programs like Excel) and data communication.

Salary: Data analysts tend to be the least compensated among the data science roles, with an average salary of around $65k USD. This is largely because data analysis is more of an entry-level role that calls upon less of the skillset needed in data science.

Sample Job Posting: Stripe helps process payments across the web for some of the largest web platforms in the world. Their data analyst position calls for somebody who is excited to apply their analytical skills to understand user behavior–and who will work closely with business and product teams to answer important data questions.

Typical Majors: Business, economics, statistics

Open Job Positions on Indeed.com: ~95,000

Industries that are Hiring Data Analysts: Consulting, healthcare, banking

Top Hiring Locations in the United States: New York City, Washington DC, Chicago

Things You’ll Catch Them Saying: “Microsoft Excel is so slow today!”

아래의 4개 서브셋로 (포커스로) 구성

• 비지니스 혹은 현장문제를
  1. 데이터와 관련된 문제로 전환하여
  2. 수학적 혹은 통계학적 모델을 세우고
  3. 데이터를 이용하여 분석한 후 이를 검증할 수 있는 능력이 필요함.
• 통계학자, 데이터매니저 등이 이에 포함될 수 있음

Required Skills and knowledges

• 수학통계
• 알고리즘,
• python
• r

Recommend sub-majors

• 수학통계
• 물리학
• Computer Science
• 경제학(수학적 모델링 + 경제이론)

데이터엔지니어는

• 대량의 정형 혹은 비정형 데이터를
• 소프트웨어엔지니어링 스킬을 이용하여 관리할 수 있는 능력이 필요. 또한
• 데이터를 수집할 수 있는 아키텍쳐를 설계하고 구성하는 능력 또한 포함

Required skills and knowledges

• Java
• Python
• SQL
• NOSQL
• Hadoop
• Spark

• 데이터분석을 통해 클라이언트에게 결과를 포장하여
• 프레젠테이션하는 것에 촛점을 둠

RSK

• Business theory and practice
• Psychological theory and knoweldges
• Excel (data manipulation)
• statistical knowledge
  • SPSS
  • SAS
  • r
• Visualization skills and tools
  • Java
  • python
  • r
  • various tools

Recommended sub-majors

• 심리학
• 경제 경영학
• 광고학 PR학 (커뮤니케이션)