A Data Scientist is someone curious, who can stare at data and spot trends. It’s nearly kind of a Renaissance individual who wants to be told and convey change to a corporation.

How can we get the value from this avalanche of data in every sector within the economy?

Well, we get persistent and data-mad personnel skilled in maths, stats and programming to weave magic using reams of letters and numbers.

There’s never been an improved time to be told the data analytics and enter the workforce as a data scientist. The work landscape is promising, opportunities span multiple industries and also the nature of the work often allows for remote work flexibility and even self-employment.

Data science roles and responsibilities are varied and the skills needed for them vary significantly. Here, we've delineated the various data science roles in conjunction with the ability set, technical information and mind-set required to hold it.

THE DATA SCIENTIST

A data scientist is perhaps one in all the most popular job titles that you simply can be placed on your card, and also the closer you get to geographic region, the more valuable this role becomes. He/she masters a full range of skills and abilities going from having the ability to handle the data, analyzing that data with the assistance of statistical techniques, to share his/her insights with his peers in an exceedingly compelling way.

SKILLS REQUIRED TO BECOME A DATA SCIENTIST:

Experience in programming languages like R, SAS, Python, MATLAB, SQL, Hive, Pig, Spark.

Experience in distributed computing and predictive modeling.

Good Experience in math, statistics and machine learning.

DATA ANALYST

Data analysts are of tasks including visualization, and processing of massive amounts of information. They even have to perform queries on the databases from time to time. One in all the foremost important skills of an information analyst is optimization. This is often because they need to make and modify algorithms that will be accustomed to cull information from a number of the largest databases without corrupting the information.

SKILLS REQUIRED TO BECOME AN DATA ANALYST

Experience in programming languages like SQL, R, SAS, Python. Certification in these can boost your job applications.

Problem-solving skills.

STATISTICIAN

Statisticians collect, organize, present, analyze, and interpret data to succeed invalid conclusions and make correct decisions. They are the key players in ensuring the success of companies involved in research, transportation, development, finance, forensics, sport, internal control, environment, education, and also in governmental agencies. plenty of statisticians still enjoy their place in academia and research.

SKILLS REQUIRED TO BECOME A STATISTICIAN:

Experience in R programming, MATLAB, SAS, Python, Stata, PIG, Hive, SQL, and Perl.

Strong background in statistical theories, machine learning and data processing and munging.

Experience in solving and analytical skills.

MACHINE LEARNING ENGINEER

Machine learning (ML) has become quite a booming field with a mind-boggling amount of information we have to top into. However, the work profile comes with its challenges. Having in-depth knowledge in a number of the foremost powerful technologies like SQL, REST APIs, etc is required. Machine learning engineers also are expected to perform A/B testing, build data pipelines, and implement common machine learning algorithms like classification, clustering, etc.

LET US LOOK AT THE SKILLS REQUIRED TO BECOME A MACHINE LEARNING ENGINEER:

Experience in programming languages like Java, Python, JS.

Strong grasp of statistics and arithmetic.

DATA ARCHITECT

A Data architect creates the blueprints for data management so the information bases will be easily integrated, centralized, and guarded with the simplest security measures. They also make sure that the engineers have the simplest tools and systems to figure with.

SKILLS REQUIRED TO BECOME AN DATA ARCHITECT:

Experience in data warehousing, Data modeling, Extraction transformation and load (ETL).

Experience in programming languages like Hive, Pig, and Spark, etc.

6. DATA AND ANALYTICS MANAGER

A data and analytics manager oversees the information science operations and assigns the duties to their team in line with skills and expertise. Their strengths should include technologies like SAS, R, SQL, etc. And in fact management.

Skills required to become an Analytics Manager:

Experience in programming like Python, SAS, R, Java.

Excellent social skills and leadership qualities, and out of the box thinking attitude.

7. BUSINESS ANALYST

This is probably the least technical profile mentioned in the list. However, the business analyst compensates for this lack of technical knowhow with a profound understanding of the various business processes that are in place. A business analyst therefore often performs the role of the middle person between the business folks and the techies. Organizations searching for business analysts are companies like Uber, Dell and Oracle.

Skills required becoming a Business analyst:

Experience in visualization in Data tools.
Understanding of Business Intelligence and Data modeling.

CONCLUSION-

Data science is emerging as a field that’s revolutionizing science and industries alike. Work across nearly all domains is becoming more data-driven, affecting both the roles that are available and also the skills that are required.