Data scientists work in tandem with data analysts, data engineers, business intelligence specialists, and data architects to create and maintain databases, analyze data, and communicate business insights. Their job is to identify the data analytics problems that offer the greatest opportunities to the organization.

Data science is an extremely broad field, entailing everything from cleaning data to deploying predictive models. It s rare for a data scientist to do it all. Most data scientists specialize in a specific function within the data processing cycle.

Data Scientist Role and Responsibilities

Data scientists work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals. They design data modeling processes, create algorithms and predictive models to extract the data the business needs, and help analyze the data and share insights with peers.

Some common data scientist responsibilities include:

Problem definition

The problem statement is the most crucial step towards solving any data analytics problem. Data scientists need to think of the problem statement in mathematical terms. For example, Why is product X underperforming and What data on user behavior might help explain it

Data collection and wrangling

Data wrangling is the process of cleaning, restructuring, and enriching raw data to make it analyzable. The primary goal of data wrangling is to reveal a deeper intelligence by gathering data from multiple sources and organizing the data for a broader analysis.

Exploratory analysis

Exploratory data analysis postpones any initial assumptions, hypotheses, or data models; instead, data scientists seek to uncover the underlying structure of the data, extract important variables, and detect outliers and anomalies.

Data processing

The data processing cycle refers to the set of operations used to transform the data into useful information. In this stage, the data is entered into a system, such as a CRM like Salesforce or a data warehouse like Redshift so that a data processing cycle can be established. Next, this process is deployed as a repeatable data model to enable long-term data analytics projects.

Model training and deployment

Data modeling represents the way data flows through a software application or the data architecture within an enterprise. It s almost like a blueprint that establishes relationships between different business entities to show how data is collected and stored.

Documentation, visualization, and presentation

Data scientists are expected to document their processes, providing sufficient descriptive information about their data for their own use as well as their colleagues and other data scientists in the future. Visualization is perhaps the most crucial aspect of the data function since computational statistics are only meaningful if they can be understood and acted upon by the organization.

There are several important Job Roles in Data Science most important one are:

It is not required to have a Programming background, although desirable. However, those without Programming background will undergo Pre-requisite training on Programming to accelerate the learning when the Program begins.

Most data scientists use the following core skills in their daily work:

Statistical analysis

Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.

Machine learning

Implement algorithms and statistical models to enable a computer to automatically learn from data.

Computer science

Apply the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering.

Programming

Write computer programs and analyze large datasets to uncover answers to complex problems. Data scientists need to be comfortable writing code working in a variety of languages such as R, Python, and SQL.

Data storytelling

Communicate actionable insights using data, often for a non-technical audience.

VERSION 1 SELF-PACED ONLINE

When can you take

Take anytime, Self-paced

Certification included

Tableau Desktop Certified Specialist certification from Tableau (Training included)

Apply now

VERSION 2 LIVE TRAINING ONLINE

When can you take

Batch starts Jan 7, 2022

Certification included

A A Certificate from Christ University

B Tableau Desktop Certified Specialist certification from Tableau (Training & Examination costs included)

Apply now

Peer networking

In addition to the training program, you will have ample opportunity to network with the peers in your cohort. Prior to coming to the program, you will have access to your cohort where you can meet and engage with your peers before, during, and after the program.

Industry networking

Throughout the program, you will be taught and mentored by Data Scientists working/having worked with leading companies.

Alumni networking

Besides, after the program, you will be invited to join the Data Science Alumni group.

Placement Leads

We have networks with leading industry participants including banks, financial institutions, consulting firms and analytics firms; you can leverage that network for connecting with the industry and finding suitable opportunities in Data Science. Once you are trained and ready, we will help you with placement leads that can help you land your dream role in Data Science.

Having said that, its entirely your performance and skill-sets that will define your journey in landing your dream job. We cannot guarantee that you will get a job after completing the program. Obtaining a job is strictly based off one s own skill sets. Upon completion of the program, we will provide you with a certificate that you can print and/or add to your LinkedIn profile.

Networking opportunities

You will have great networking opportunities at the program. Our industry faculty work in the industry in leading positions and that will provide a great opportunity for you to network. Besides, EduEdgePro, through its vast industry network, will help you reach out to the leading financial firms for placements.