Data Science is one of the hottest topics at the present time, if you want to go into the data science field then this article will help you to outline which data science job title is good for you because of the different jobs available in the field of data science.
A career in the data science field has several benefits and a high salary is one of them as we know that numerous exciting opportunities in the data science technology field are available.
In this article, we have discussed the Top 8 Data Science Jobs and covered the required skills and average salary for that role.
No.1: Data Scientist
A data scientist is responsible for extracting insights from data and making them useful. This includes structured and unstructured data. As we know, A data scientist must be able to clean and prepare data for analysis, build predictive models, communicate their findings to stakeholders and process large data sets and uncover useful patterns, insights, and trends in the data.
Skills:
- Statistical analysis and computing
- Machine learning
- Data visualization
- Deep Learning
- Communication
- Business acumen
- Data Wrangling
- Processing large data sets
Salary:
- $120,500 is the Average Salary for a data scientist.
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No.2: Data Analyst
A Data Analyst is responsible for turning data into actionable insights or useful insights by using different tools. This includes cleaning and preparing data for analysis, performing exploratory data analysis, and creating reports and dashboards. A data analyst must be able to communicate their findings effectively to stakeholders. It has always been considered one of the best data science jobs in India and at least one bachelor's degree is required.
Skills:
- Data management
- Structured Query Language
- Data analysis
- Data visualization
- Machine learning
- Communication
- Statistical visualization
Salary:
- $76,500 is the Average Salary for a data analyst.
No.3: Data Engineer
A data engineer is responsible for building and maintaining systems that collect, store, and process data. This includes designing, building, and optimizing data channels, developing data models, and building data warehouses. A data engineer must have strong technical skills, and communication skills and be able to work with large data sets. They are also responsible for maintaining and building the necessary structures to store and access historical records.
Skills:
- Database Tools
- Data Engineering
- Data ingestion tools
- Database design
- Data modeling
- Big data
- Machine Learning skills
Salary:
- $96,500 is the Average Salary for a Data Engineer.
No.4: Data Warehouse Architect
Data warehouse architects are presented as a specialized subfield of data engineering for people interested in working with organizational data storage systems. The Data Warehouse Architect job role requires knowledge of SQL and a strong command of other technical skills. The skills required may also vary depending on the specifications and requirements of the employer.
Skills:
- mathematics and statistics
- Data analysis
- DBMS
- SQL Server
- Communication
- Database and cloud computing design
Salary:
- $145,500 is the Average Salary for a Data Warehouse Architect.
No.5: Business Analyst
A business analyst is responsible for turning data into tangible insights. This includes cleaning and preparing data for analysis, performing exploratory data analysis, and creating reports and presentations. A business analyst must be able to effectively communicate their insights to stakeholders. The job of a business analyst involves collecting, analyzing, and making recommendations based on company data.
Skills:
- Python
- Data analysis
- DBMS
- Data visualization
- Communication
- Business acumen
Salary:
- $75,500 is the Average Salary for a business analyst.
No.6: Machine Learning Engineer
ML engineers are responsible for creating and implementing machine learning models. This includes data pre-processing, model design and training, and model hyperparameter tuning. An ML engineer must have strong technical skills, communication skills, and be able to work with large data sets. Major technicians hire these professionals in positions with degrees such as research scientists or research engineers.
Skills:
- Python
- Machine learning
- Data Engineering
- Deep Learning
- Data modeling
- Big data
- Data Analyst
Salary:
- $110,500 is the Average Salary for an ML Engineer.
No.7: Quantitative Analyst
Quantitative analysts are usually referred to as "quants". You will be solely responsible for using state-of-the-art statistical analysis and tools to solve problems, answer questions and make future predictions regarding risk management and finance.
Skills:
- Object-oriented programming
- Big data modeling
- Machine learning
- Data mining
- Python
- SQL
Salary:
- $145,500 is the Average Salary for a Quantitative Analyst.
No.8: MLOps Engineer
An MLOps engineer is responsible for building and maintaining systems that implement and maintain machine learning models. This includes continuous integration (CI) / continuous delivery (CD) pipeline development and management, model performance monitoring, and model deployment management. MLOps engineers must have strong technical skills and be able to work with large data sets.
Skills:
- AWS, Azure, or GCP
- Docker and Kubernetes
- MLOps pipelines
- Machine learning
- Data Engineering
- DevOps
- Big data
- Keras, PyTorch, Tensorflow
Salary:
- $120,500 is the Average Salary for an MLOps engineer.
Conclusion:
If you want to go into the Data Science field then this article will help you to understand which type of job is best for me in Data Science. We have outlined the 8 Data Science jobs, roles, skills, and average salaries.
You should also check out, Django Developer Roadmap, Python Developer Roadmap, C++ Complete Roadmap, Machine Learning Complete Roadmap, and Laravel Developer Roadmap.
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