The Data Scientist job has emerged as one of the top marketable and in-demand professions. Businesses and organizations across the world recognize the power of data and the need to manipulate data most accurately. The efficient use of data/big data lies in the competency of a data science analyst known as a Data Scientist. The Data Scientist skills and prowess is critical for manipulating vast and unstructured data sources and deriving insights from the data. Data scientists are hard to find and keep, but any company that wants to benefit from big data will need their expertise.

No doubt, the challenges that organizations face are to identify the talent and make productive use of the skills. A comprehensive idea of what data scientists do will make the job easier and equally help Managers responsible for hiring in identifying talents. Let us throw light on the data scientist roles and responsibilities, the skills required to perform their power over data, and the data scientist salary structure to give aspiring candidates a broad overview of what to expect from pursuing a career as a Data scientist.

Data Scientist Roles and Responsibilities

Data scientist skills are essential for organizations to take advantage of the possibilities that data offers. The data scientist roles and responsibilities are critical for any organization in today’s data-driven world. Data Scientists give data structure, sift through it for compelling patterns, and offer executives advice on how these implications might affect decisions about processes, decisions, and goods. They uncover the narrative hidden in the data and share it. Additionally, they don’t just give reports; instead, they probe the issues at hand and come up with novel solutions. For instance, one data scientist investigating a scam issue discovered it was comparable to a specific DNA sequencing issue. By fusing these various worlds, he created a method that significantly decreased fraud losses.

We can summarize the data scientists roles and responsibilities in the following points:
• Identifying sources of data and extracting useful data sources collectively known as Data mining
• Selecting features, developing classifiers, and optimizing them by applying machine learning tools
• Doing structured and unstructured data preparation and analyzing them
• Discovering trends and patterns by combining various modules and algorithms
• Improving data-gathering processes to capture all pertinent data for collecting analytical systems
• Preparing, cleansing, and guaranteeing the accuracy of data for analysis.
• Discovering patterns and solutions by analyzing a lot of data
• Developing machine learning algorithms and prediction systems
• Clear presentation of the results.
• Provide tactics and ways to deal with company difficulties.
• Link up with the business and IT departments

Data Scientist Skills

Organizations are increasingly depending on data scientist skills to maintain, grow, and remain one step ahead of the competition, regardless of their goals whether to improve customer retention, streamline the product development process, or mine data to find new business opportunities.
The data scientist skills requirement may be classified into two categories:
Technical and Non-Technical Skills

Technical Data Scientist Skills

Data Scientists are required to possess the following technical skills to perform and be successful data scientists:
• Statistical analysis and computing
• Machine Learning
• Deep Learning
• Processing large data sets
• Data Visualization
• Data Wrangling
• Mathematics
• Programming
• Statistics
• Big Data

A Ph.D. or Master’s degree in statistics, computer science, or engineering is held by some data scientists. Any aspiring data scientist can benefit from this educational background because it gives them a solid foundation and shows them the fundamental Big Data and data scientist skills they need to be successful in their career. Some universities now provide specialized programs designed to meet the educational requirements for pursuing a job in data science, allowing students to concentrate on the subject they are interested in a shorter duration.

Major Technical Data scientist Skills

Programming

A data scientist aspirant is required to have comprehensive knowledge of a variety of programming languages like SQL, Python, Java, SQL, C/C++, etc. With such potential data, scientists can work their way to organize unstructured data sets.

Mastery of Analytical tools like SAS

Another important technical data scientist skills requirement is to have the prowess of handling analytical tools to extract valuable information. Some of the commonly used tools are SAS, R, Hadoop, Hive, Spark, etc. The best way to establish expertise in these tools is to sign up for a certification course.

Proficient with Unstructured Data sets

Data scientists need to have prior experience working with unstructured data from various sources and platforms. For instance, a data analyst should be skilled at managing social media if they are working on a project to assist the marketing team in providing insightful research. Artificial Intelligence, Machine learning, Deep learning, probability, and statistics are some other data Scientist skills.

Non-Technical Data Scientist Skills

These non-technical data scientist skills are personal abilities that can be challenging to evaluate solely by looking at the educational background, credentials, etc. Let us discuss them briefly:

Excellent Business Acumen

An effective application and results can be derived when you combine technical skills with sound business judgment. In the absence of such potential, a budding data scientist might not be able to identify the issues and possible difficulties that must be overcome for a company to advance. This is crucial for assisting the company you work for in pursuing new business possibilities.

Powerful communication abilities

Communication is the next talent that is mandatory as one of the data scientist skills. Experts at extracting, understanding, and analyzing data are known as data scientists. Coupled with this expertise, one must be able to explain and transmit the information to the team members who hail from varied professional backgrounds for a successful career.

Great Instinct for Data

Having great intuition data is another critical data scientist skill that a professional must possess. An experienced data scientist has insight and knows when to delve further for valuable data insights. Huge data sets may not always produce valuable data insights. This boosts data scientists’ productivity, and it can be mastered with practice and the right training.

Data Scientist Salary

While the Data scientist salary package may vary from company to company and also several other factors including region and experience level, Data scientists are known to earn attractive pay packages annually in addition to several other attractive perks.
The data scientist salary in the different states of the US are: New York - $132,826
New Hampshire - $128,704 California - $127,388
Vermont - $121,599 Idaho - $120,011
Massachusetts - $119,234 Washington - $116,118
Hawaii - $115,887 Data scientist job is still going to lead the technological sphere with their unrivaled advances. Data scientists perform a key role in bringing innovative changes in the world. Start your career today and become an influential leader.