Data Scientists
Data scientists use their advanced statistical skills to help improve the models the data engineers implement and to put proper statistical rigour on the data discovery and analysis the customer is asking for. Essentially the business analyst is just one of many customers in mobile gaming most of the questions come from game designers and product designers’ people with a subject matter expertise very few data scientists can ever reach.
But they don’t have to. Occupying the space between engineering and subject matter experts, data scientists can help both by using skills no one else has without having to be the unicorn.
- Data Engineer
Data Engineer either acquires a master’s degree in a data-related field or gather a good amount of experience as a Data Analyst. A Data Engineer needs to have a strong technical background with the ability to create and integrate APIs. They also need to understand data pipelining and performance optimization.
- Data Analyst
Most entry-level professionals interested in getting into a data-related job start off as Data analysts. Qualifying for this role is as simple as it gets. All you need is a bachelor’s degree and good statistical knowledge. Strong technical skills would be a plus and can give you an edge over most other applicants. Other than this, companies expect you to understand data handling, modeling and reporting techniques along with a strong understanding of the business.
Different skill sets required for Data Analyst, Data Engineer and Data Scientist:
Data Analyst vs Data Engineer vs Data Scientist Skill Sets | ||
Data Analyst | Data Engineer | Data Scientist |
Data Warehousing | Data Warehousing & ETL | Statistical & Analytical skills |
Adobe & Google Analytics | Advanced programming knowledge | Data Mining |
Programming knowledge | Hadoop-based Analytics | Machine Learning & Deep learning principles |
Scripting & Statistical skills | In-depth knowledge of SQL/ database | In-depth programming knowledge (SAS/R/ Python coding) |
Reporting & data visualization | Data architecture & pipelining | Hadoop-based analytics |
SQL/ database knowledge | Machine learning concept knowledge | Data optimization |
Spread-Sheet knowledge | Scripting, reporting & data visualization | Decision making and soft skills |