Five Lucrative Job Roles In Data Science

Five Lucrative Job Roles in Data Science

by Niti Sharma — 4 years ago in Top 10 3 min. read
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Data Science is a multi-disciplinary field where several disciplines like Statistics, Machine Learning, Data Analysis, Computer Science, and other related fields are combined together. Accordingly, there are diverse sets of job roles in the data science industry today. The roles are evolving as per the organization’s demands as they emphasize different skills over others.  To mention a few, they are data engineers, business analysts, machine learning engineers, big data engineers, statisticians, database administrators, data scientists, and more.

Let’s have a quick rundown on five exciting data science professionals’ roles here.

Different Job Roles in Data Science Industry

1.Data Engineer/Architect

Job Profile:

They design, build and manage big data infrastructure. They ensure that the data ecosystem of the organization is running smoothly so that data scientists can carry on with their analysis work anytime without interruption.

Skills Required:

  • Language Proficiency: R, Python, C++, Java, SAS, MATLAB, Perl, Ruby, and SPSS.
  • Working knowledge of Hadoop, MapReduce, Pig, MySQL, NoSQL, SQL, Hive, Cassandra, data streaming and programming.
  • Data APIs, ETL tools, data warehousing solutions, and data modelling.

Roles and Responsibilities:

  • Collect and store data
  • Develop, test, and maintain scalable data management systems
  • Seamlessly integrate new data management technologies
  • Conduct real-time or batch processing
  • Custom software components and analytics
  • Handle errors efficiently

PayScale:

An entry-level data engineer earns an average salary of $77,487. An expert in the field can expect $114,619.

2. Database Administrator

Job Profile:

The Database administrators (DBA) handle extremely sensitive data. They ensure the creation, availability, storage, protection, and retrieval of data as required.

Skills Required:

  • Knowledge of database queries, theory, design
  • MySQL or MS-SQL Server
  • SQL, PSM, Transact-SQL
  • Distributed computing architectures
  • Operating systems, storage technologies, and networking
  • Maintenance, recovery and handling database failover

Roles and Responsibilities:

  • Installs and assists installation of systems/applications
  • Monitors database resources
  • Updates hardware/software and services
  • Maintains standard security measures
  • Monitors technology and regulations changes
  • Remodels and upgrade projects

PayScale:

An entry-level DBA can expect an average salary of $70,637, whereas an expert earns an average of $94,500.

3. Data Analyst

Job Profile:

They are more generalists and play varied roles. They are involved in acquiring humongous data, processing, summarizing, and reporting them.

Skills Required:

  • Microsoft Excel, Access, and SharePoint
  • SQL databases
  • R, Python, HTML, SQL, C++, and JavaScript
  • Business Intelligence concepts
  • Data visualization and data warehousing

Roles and Responsibilities:

  • Collect, analyse, and report data
  • Improve data collection, analysis, and reporting by identifying new data resources and methods
  • Collect customer requirements and design reports

PayScale:

The average salary for a data analyst is $84,955

4. Machine Learning Engineer

Job Profile:

They must be an expert in using algorithms, wrangling codes and churn datasets.

Skills Required:

  • Python, Java, Scala, C++, and JavaScript
  • Machine learning concepts and big datasets
  • Mathematics and Statistics
  • SQL, AWS, Rest APIs, Elasticsearch

Roles and Responsibilities:

  • Design and implement machine learning applications
  • Build data pipelines and conduct A/B testing
  • Benchmark infrastructure and improve data quality
  • Ensure the reliability of machine learning systems

PayScale:

The average salary ranges between $97,070 to $179,010.

5. Statistician

Job Profile:

The statistician is responsible to collect, organize, present, analyse, and interpret data for making informed decisions.

Skills Required:

  • Higher degree in Statistics/Mathematics
  • R programming, MATLAB, SAS, Hive, SQL, Perl, Pig, and Python
  • Strong background in machine learning, data visualization, and mining

Roles and Responsibilities:

  • Use tools to analyse, identify patterns, relationships, or trends
  • Interpret results with recommendation and predictions
  • Ensure data quality
  • Devise new programs/models

PayScale:

The average salary ranges from $69,869 to $106,096.

To summarize, the roles and responsibilities are different with an emphasis on special skills. These roles are equally exciting and upgrading your skills is the best way forward.

Niti Sharma

Niti Sharma is a professional writer, a blogger who writes for a variety of online publications. She is also an acclaimed blogger outreach expert and content marketer. She loves writing blogs and promoting websites related to technology sectors.

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