A Data scientist is someone who makes value out of data. Such a person proactively fetches information from various sources and analyzes it for better understanding about how the business performs and builds AI tools that automate certain processes within the company.
Data Scientist 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 modelling processes, create algorithms and predictive models to extract the data the business needs, then help analyze the data and share insights with peers. While each project is different, the process for gathering and analyzing data generally follows the below path:
- Ask the right questions to begin the discovery process.
- Acquire data.
- Process and clean the data.
- Integrate and store data.
- Initial data investigation and exploratory data analysis.
- Choose one or more potential models and algorithms
- Apply data science methods and techniques, such as machine learning, statistical modelling, and artificial intelligence.
- Measure and improve results.
• Proven experience as a Data Scientist or Data Analyst
• Experience in data mining
• Understanding of machine-learning and operations research
• Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset
• Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
• Analytical mind and business acumen
• Strong math skills (e.g. statistics, algebra)
• Problem-solving aptitude
• Excellent communication and presentation skills
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or another quantitative field is preferred
Common Data Scientist Job Titles :
The most common careers in data science include the following roles.
• Data scientists: Design data modelling processes to create algorithms and predictive models and perform custom analysis.
• Data analysts: Manipulate large data sets and use them to identify trends and reach meaningful conclusions to inform strategic business decisions.
• Data engineers: Clean, aggregate, and organize data from disparate sources and transfer it to data warehouses.
• Business intelligence specialists: Identify trends in data sets.
• Data architects: Design, create, and manage an organization’s data architecture.
Data Science Career Outlook
By many accounts, becoming a data scientist is a highly desirable career path. For four years in a row, Glassdoor ranked data scientists as one of the 10 best jobs in America, based on median base salary, the number of active job openings, and employee satisfaction rates. Likewise, Harvard Business Review called data science “the sexiest job of the 21st century,” noting that “high-ranking professionals with the training and curiosity to make discoveries in the world of big data” are in major demand.
From start-up’s to Fortune 500s to government agencies, organizations are seeing the value in capitalizing on big data. Google’s Chief Economist Hal Varian spoke about the need for data scientists back in 2009, telling McKinsey Quarterly, “the ability to take data to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it that’s going to be a hugely important skill in the next decades.”
This prediction proved prescient. LinkedIn calls data science the most promising job of 2019. The job site Indeed.com recently shared statistics about the surge in data science career opportunities.
Data Scientist Salaries
In India :- It Depends on Experience Fresher got 7–12 Lakhs and Those having 5–8 years experience They Got 10–30 Lakhs Salary
Essential Data Science Skills
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 Java, R, Python, and SQL.
• Data storytelling: Communicate actionable insights using data, often for a non-technical audience.
Data scientists play a key role in helping organizations make sound decisions. As such, they need “soft skills” in the following areas.
• Business intuition: Connect with stakeholders to gain a full understanding of the problems they’re looking to solve.
• Analytical thinking. Find analytical solutions to abstract business issues.
• Critical thinking: Apply objective analysis of facts before coming to a conclusion.
• Inquisitiveness: Look beyond what’s on the surface to discover patterns and solutions within the data.
• Interpersonal skills: Communicate across a diverse audience across all levels of an organization.
Starting a Career in Data Science-
Most employers look for data science professionals with advanced degrees. Candidates for data science roles usually begin with a foundation in computer science or math and build on this with a master’s degree in data analytics. In these graduate-level programs, professionals gain core competencies in skills such as predictive analytics, statistical modelling, big data, data mining applications, enterprise analytics, data-driven decision making, data visualization, and data storytelling.
Earning a Degree in Data Analytics Coding Blocks
Studying data analytics teaches students how to employ statistics, analytics systems technology, and business intelligence to achieve specific goals. With this foundational knowledge, students discover how to find a logical, data-driven path to resolving a complex problem. They also learn how to overcome data obstacles, such as dealing with uncertain data sets and reconciling data from disparate sources.
The Master of Professional Studies in Analytics program at Coding Blocks prepares students by learning various courses provided by coding blocks and if need any support then experts are always there to help you and solve your problem. We have also DATA SCIENCES MASTER COURSE so you can do this and make your future better and reserve your position as a data scientist in Industry
Bhargav A. Joshi