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Data science is a multidisciplinary blend of data inference, algorithm enhancement and development and employing technical software or other such tools in order to solve analytically complex problems. The theories and subjects data science takes into account while engineering an effective model are mathematics, statistics, information science, computer science and machine learning. At its core, the aspect about data science or data analytics is that it is about dwelling into the data at the grass root level to try and create predictive models and understand trends which enable companies to make better decisions and generate business value. Data Science is a more forward-looking approach, an exploratory way with the focus on analyzing the past or current data and predicting the future outcomes with the aim of making informed decisions. It answers the open-ended questions as to “what” and “how” events occur.
Skills required for data science: -
To get a job in data science or analytics it is crucial that a person is proficient in the following skills: -
1. Education – They should have at least a master’s degree and 50% of the data scientists/analysts even have a PhD degree. A bachelor’s degree in computer science, statistics, mathematics or any other relevant field is mandatory.
2. Python coding - It is the most common programming language required in data science related fields.
3. R programming - It is a prominent programming language which is used to solve analytical and complex problems.
4. SQL Database/Coding - SQL (structured query language) is a programming language that can help you to carry out operations like add, delete and extract data from a database.
5. Machine learning and AI - Data scientists work with big data sets.
6. Data visualization - More often than not the data presented is not in a comprehensive manner. Data visualization gives organizations the opportunity to work with data directly. They can quickly grasp insights that will help them to act on new business opportunities and stay ahead of competitions.
Top 7 paying data science jobs :-
1. Big data engineer- He/she is responsible for analyzing large amounts of data and changing it so that it can be used for valuable insights that are assigned to them by the top executives who require them to enhance their business. Their primary focus is to find optimal solutions maintaining and implementing them and finding a way to integrate them in the architecture which is used across the company. They have a very wide range of tasks which they need to accomplish in generating effective and comprehensive
data. The fact that they have to cater and tackle large data sets whilst being proficient in a number of complicated software such as Hadoop v2, HDFS and other relevant platforms, the salary range varies from $135,000 to $196,000.
2. Data architect- This is a fairly intriguing field which requires a person to define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way. They should be able to understand the system development cycle, software project management approaches, requirement design and test techniques. In addition to depth in established data management and reporting technologies, the data architect is either experienced or conversant in emerging tools like columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data. While not necessarily deep in all of these technologies, the data architect hopefully is experienced in one or more, and must understand them sufficiently to guide the organization in understanding and adopting them. The annual salary ranges from $131,000 to $187,000.
3. Database manager- A database manager either works in house or for a range of clients to develop, maintain and manage a range of databases. Often, they are required to find the most optimized ways to store and record data depending on the requirements of the company or firm. They need to use relevant software which would keep the data dynamic for updating and editing. SQL is one of the best portals to carry out analytical and organizational jobs. A database manager must have an eye for accuracy as any discrepancy in the original and entered data can cost the company a huge deal. They need to collaborate with the other departments regarding the connection of one faculty with the order. There is a chain of passing the data to the next authority in line which means that a DBM must generate the outcome such that it is not only compact and comprehensive for the end user (the firm) but also all the stakeholders who will need to interpret or use the data at some point. The average salary range varies from $120,000 to $145,000.
4. Business intelligence analyst- A business intelligence analyst directly works to analyze and mold information from the data in such a manner that it serves a specific purpose to provide new and intelligent solutions. The analyst requires a strong command over information technology in order to bear the most fruitful results. Along with this they help the companies to prosper by crafting long term business plans or blueprints to prevent the once committed mistake. Once they plot the data in a representative manner they can trace it to the beginning of the implementation chain wherein they could detect the fallacy. They work in close collaboration with the developers as they suggest them ways to enhance and amp up the overall software. It’s a role that combines hard skills like programming, data modeling and statistics with soft skills like communication, analytical thinking and problem-solving. The salary range for this data science job is $118,000 to $145,000.
5. Digital marketing manager- A digital marketing manager is responsible for developing, managing and implementing marketing campaigns to promote a company’s product or
services. Digital marketing employs various digital tactics that has its specific value and separate campaigns. They conduct market surveys and analyze the data to use it for refining the user’s experience. Content marketing, referral program launching, search engine optimization etc. lie at the core of the digital market. Search engine optimization goes hand in hand with the content marketing end. It is a method of increasing the traffic on your website by making it visible in the search results. The achievement of SEO is that it instills a sense of reliability in the users which makes your website noticeable. Understanding the algorithm and mechanism of the same is the only way to create a long lasting effective results. Relevant keyword identification and structural tweaks might appear minor but they have copious benefits in the overall marketing. They operate by studying the trends from user data and aim to create a seamless end result which is beneficial for both the users and the company. The average salary ranges usually between $83,015-$119,106.
6. Statistician- A statistician is someone who is well equipped with various statistical theories and methods and applies them to analyze and interpret quantitative data. One of the most interesting facts about this profession is that statistics is applied to a vast number of fields and hence they have a huge job market. Statistician are prominently employed in firms that deal with market research/public opinion. They are also employed in departments dealing with quality control and product development. Entry level job as statistician requires you to hold at least a bachelor’s degree in statistics. A master’s degree in statistics/mathematics/survey methodology, might land you a prestigious job profile. However, a research professional or an academician are required to get their PhD. A statistician tackles technical responsibilities like collecting data using appropriate strategy, analyzing and interpreting data using software tools like R, SAS, SPSS etc., presenting interpreted information in an appropriate format for diverse audiences, developing statistical tools, programs and databases, monitoring data quality etc. Average package of a statistician varies from $64,230 to 108,500.
7. IT system analyst - An IT system analyst works with companies/institutions/independent clients to diagnose database issues, resolve user complaints and pitch system innovations to the management to optimize efficiency. A system analyst is required to be equipped with certain key skills like, system administration, business analysis, technical analysis, Microsoft Office, SQL, project management etc. Entry level jobs in this profession require a candidate to have at least a bachelor’s degree in computer science and related domains. As system analysts communicate with various community/institution members to help them with accessing computer systems, sufficient intrapersonal communication skills are a requirement. Thus, various companies encourage candidates with majors in liberal arts or business administration. Certifications or work experience from organizations like Microsoft and IBM boost your potential as a system analyst. A system analyst’s salary usually ranges between $59,000-$81,000.
Conclusion: -
In today’s technology driven world where almost every major task is automated, data science acts as a boon. It helps people interpret and thus analyze the data trends of their companies to generate stronger business plans for them as well to comprehend the requirements of the end user to bring to them a valuable end product which fits their parameters. The aforementioned jobs are at the top priority of employers as they look for those who are skilled in the relevant areas such as computer science, data analytics, data visualization, information technology etc.
Skills required for data science: -
To get a job in data science or analytics it is crucial that a person is proficient in the following skills: -
1. Education – They should have at least a master’s degree and 50% of the data scientists/analysts even have a PhD degree. A bachelor’s degree in computer science, statistics, mathematics or any other relevant field is mandatory.
2. Python coding - It is the most common programming language required in data science related fields.
3. R programming - It is a prominent programming language which is used to solve analytical and complex problems.
4. SQL Database/Coding - SQL (structured query language) is a programming language that can help you to carry out operations like add, delete and extract data from a database.
5. Machine learning and AI - Data scientists work with big data sets.
6. Data visualization - More often than not the data presented is not in a comprehensive manner. Data visualization gives organizations the opportunity to work with data directly. They can quickly grasp insights that will help them to act on new business opportunities and stay ahead of competitions.
Top 7 paying data science jobs :-
1. Big data engineer- He/she is responsible for analyzing large amounts of data and changing it so that it can be used for valuable insights that are assigned to them by the top executives who require them to enhance their business. Their primary focus is to find optimal solutions maintaining and implementing them and finding a way to integrate them in the architecture which is used across the company. They have a very wide range of tasks which they need to accomplish in generating effective and comprehensive
data. The fact that they have to cater and tackle large data sets whilst being proficient in a number of complicated software such as Hadoop v2, HDFS and other relevant platforms, the salary range varies from $135,000 to $196,000.
2. Data architect- This is a fairly intriguing field which requires a person to define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way. They should be able to understand the system development cycle, software project management approaches, requirement design and test techniques. In addition to depth in established data management and reporting technologies, the data architect is either experienced or conversant in emerging tools like columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data. While not necessarily deep in all of these technologies, the data architect hopefully is experienced in one or more, and must understand them sufficiently to guide the organization in understanding and adopting them. The annual salary ranges from $131,000 to $187,000.
3. Database manager- A database manager either works in house or for a range of clients to develop, maintain and manage a range of databases. Often, they are required to find the most optimized ways to store and record data depending on the requirements of the company or firm. They need to use relevant software which would keep the data dynamic for updating and editing. SQL is one of the best portals to carry out analytical and organizational jobs. A database manager must have an eye for accuracy as any discrepancy in the original and entered data can cost the company a huge deal. They need to collaborate with the other departments regarding the connection of one faculty with the order. There is a chain of passing the data to the next authority in line which means that a DBM must generate the outcome such that it is not only compact and comprehensive for the end user (the firm) but also all the stakeholders who will need to interpret or use the data at some point. The average salary range varies from $120,000 to $145,000.
4. Business intelligence analyst- A business intelligence analyst directly works to analyze and mold information from the data in such a manner that it serves a specific purpose to provide new and intelligent solutions. The analyst requires a strong command over information technology in order to bear the most fruitful results. Along with this they help the companies to prosper by crafting long term business plans or blueprints to prevent the once committed mistake. Once they plot the data in a representative manner they can trace it to the beginning of the implementation chain wherein they could detect the fallacy. They work in close collaboration with the developers as they suggest them ways to enhance and amp up the overall software. It’s a role that combines hard skills like programming, data modeling and statistics with soft skills like communication, analytical thinking and problem-solving. The salary range for this data science job is $118,000 to $145,000.
5. Digital marketing manager- A digital marketing manager is responsible for developing, managing and implementing marketing campaigns to promote a company’s product or
services. Digital marketing employs various digital tactics that has its specific value and separate campaigns. They conduct market surveys and analyze the data to use it for refining the user’s experience. Content marketing, referral program launching, search engine optimization etc. lie at the core of the digital market. Search engine optimization goes hand in hand with the content marketing end. It is a method of increasing the traffic on your website by making it visible in the search results. The achievement of SEO is that it instills a sense of reliability in the users which makes your website noticeable. Understanding the algorithm and mechanism of the same is the only way to create a long lasting effective results. Relevant keyword identification and structural tweaks might appear minor but they have copious benefits in the overall marketing. They operate by studying the trends from user data and aim to create a seamless end result which is beneficial for both the users and the company. The average salary ranges usually between $83,015-$119,106.
6. Statistician- A statistician is someone who is well equipped with various statistical theories and methods and applies them to analyze and interpret quantitative data. One of the most interesting facts about this profession is that statistics is applied to a vast number of fields and hence they have a huge job market. Statistician are prominently employed in firms that deal with market research/public opinion. They are also employed in departments dealing with quality control and product development. Entry level job as statistician requires you to hold at least a bachelor’s degree in statistics. A master’s degree in statistics/mathematics/survey methodology, might land you a prestigious job profile. However, a research professional or an academician are required to get their PhD. A statistician tackles technical responsibilities like collecting data using appropriate strategy, analyzing and interpreting data using software tools like R, SAS, SPSS etc., presenting interpreted information in an appropriate format for diverse audiences, developing statistical tools, programs and databases, monitoring data quality etc. Average package of a statistician varies from $64,230 to 108,500.
7. IT system analyst - An IT system analyst works with companies/institutions/independent clients to diagnose database issues, resolve user complaints and pitch system innovations to the management to optimize efficiency. A system analyst is required to be equipped with certain key skills like, system administration, business analysis, technical analysis, Microsoft Office, SQL, project management etc. Entry level jobs in this profession require a candidate to have at least a bachelor’s degree in computer science and related domains. As system analysts communicate with various community/institution members to help them with accessing computer systems, sufficient intrapersonal communication skills are a requirement. Thus, various companies encourage candidates with majors in liberal arts or business administration. Certifications or work experience from organizations like Microsoft and IBM boost your potential as a system analyst. A system analyst’s salary usually ranges between $59,000-$81,000.
Conclusion: -
In today’s technology driven world where almost every major task is automated, data science acts as a boon. It helps people interpret and thus analyze the data trends of their companies to generate stronger business plans for them as well to comprehend the requirements of the end user to bring to them a valuable end product which fits their parameters. The aforementioned jobs are at the top priority of employers as they look for those who are skilled in the relevant areas such as computer science, data analytics, data visualization, information technology etc.
