|Job Role||Job Description|
|Data Analyst||Extracting data using various automated tools from various primary and secondary sources.
Removing corrupted data and fixing coding errors and related problems. Filter Data by reviewing reports and performance indicators to identify and correct code problems. Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets could be helpful for diagnosis and prediction.
Developing and maintaining databases, and data systems and reorganizing data in a readable format.
Performing analysis to assess the quality and meaning of data. Assign a numerical value to essential business functions so that business performance can be assessed and compared over periods of time.
Preparing reports for the management stating trends, patterns, and predictions using relevant data.
Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.
|Data Engineers||Work on Data Architecture, plans, Data Generation, and maintenance in alignment with business requirements.
Collecting data from various appropriate sources.
Store and optimize data.
Conduct research in the industry to address any issues that can arise while tackling a business problem.
Appropriate use and implementation of various machine learning algorithms like the random forest, decision tree, k-means, and others. Create Models and Identify Patterns existing within the Data sources etc.
|Database Administrator:||Designing and implementing databases in accordance to end users’ information needs and views.
Defining users and enabling data distribution to the right user, in the appropriate format, and in a timely manner
|Machine Learning Engineer:||Designing, developing, and researching Machine Learning systems, models, and schemes.
Studying, transforming, and converting data science prototypes.
Searching and selecting appropriate data sets.
Performing statistical analysis and using results to improve models.
|Data Scientist:||Extracting value out of data.
Acquire information from various sources and analyses it for a better understanding of how the business performs,
Build AI tools that automate certain processes within the company.
Acquiring Processing and cleaning the data. Further Integration and data storage. Initial data investigation and exploratory data analysis.
Choosing potential models and algorithms.
|Data Architect||Analyze the data needs of the company and uses skills in coding to maintain secure databases.
Collect and organize the data obtained.
A Data Architect uses their training in analytics and various coding programs to analyze information and draw conclusions based on their findings.
|Collecting, integrating, and analyzing large data sets and using statistical analysis to support decision making.
Optimizing statistical processes and providing statistical input/support where required. … Reporting results of statistical analysis in the form of graphs, charts, and tables
|Business Analyst:||Business analysts work with organizations to help them improve their processes and systems.
Conducting research and analysis in order to come up with solutions to business problems and help to introduce these systems to businesses and their clients
|Data and Analytics Manager||Developing strategies for effective data analysis and reporting.
Selecting, configuring, and implementing analytics solutions. Leading and developing a team of data analysts.
Most in-demand skills (employers lookout when hiring a data scientist) delivered by the School of Data Science are –
- Business Domain Knowledge
- Probability & Statistics
- Linear Algebra and Basics of Calculus
- Big Data Architecture
- Hadoop and HDFS
- Machine Learning
- R Programming
- Data Structure
- Database Management System
- Data Mining
- Data Visualization Tools
- Data Analysis using Spread Sheet
- Artificial Intelligence
- Deep Learning
- Apache Spark and Scala
- Data Management using Cloud
- Soft Skills