Reading is easy, comprehension is not. Hearing is easy, listening is not. Similarly, obtaining a million bytes of data is easy, but parsing through them and forming a structured format of information is not. Yes, a data scientist’s job is not comfortable, but staying in a comfort zone never changes the world.

A data scientist is an artist, mathematician and engineer, all rolled in one. Formatting an unstructured data into a structured format requires a skilled statistician.

Creating algorithms to parse and output trained models/subsets of the data expects the expertise of a machine learning engineer.

Presenting the data in a visually comprehensible and appealing manner entails the services of an artist.

When one job profile requires these many skills, it’s not hard to see why data scientists are called the current generation’s superheroes.

Now arises the million-dollar question, “Can I become a data scientist?”. Yes, you definitely can because the data science field is vast and filled with opportunities that are waiting to be utilized. In the following sections, we will analyze the data science career, the qualifications required for the same and average remuneration that can be expected etc. Armed with this knowledge, you can start on your exciting journey into the data science territory.

Data Scientist

Become a Data Scientist
  • Job description
    • Required to mine vast amounts of unstructured data, and then apply statistical learning, machine learning methodologies etc. to transform into structured data.
  • Educational requirements
    • A bachelor’s degree in a related field like Math, Physics, Computer Science, Engineering etc. (This is a compulsory pre-requisite to foray into the field)
    • A master’s degree in a field related to data science (This is not compulsory, but highly preferred to rise in the ranks within the field)
    • Online certifications (This coupled with a solid bachelor’s degree can provide an easy start in the data scientist career path)
  • Forms of employment
    • Part-Time: Not highly encouraged, but increasingly opted by individuals who love to challenge themselves with complex data problems of different kinds. Rather than get boxed into a particular form of data analysis
    • Full-Time: Widely opted form of employment which ensures stability and career growth within the chosen industry. Helps in improving skill on a particular focus area and becoming a subject matter expert in said topic.
  • Famous recruiting companies
    • IBM
    • Amazon
    • Facebook
    • Apple
    • Microsoft
    • Google
  • Average initial salary structure
    • India: 8 Lakhs per annum (INR)
    • USA: 85k per annum (USD)

Business Intelligence Developer

Business Intelligence Developer
Business Intelligence Developer
  • Job description
    • A business intelligence developer is someone who makes business data understandable to help further the development of said concern. In colloquial terms, we could say, a Business Intelligence (BI) developer is the layman’s data scientist. He/ She uses various BI tools (e.g. Power BI) to decode the obtained data sets and present it in the forms of graphs, diagrams or reports etc. in non-technical terms, that will be feasible for both the business owners and customers to understand.
  • Educational requirements
    • A bachelor’s degree (preferably in related fields like programming or computer science)
    • Experience is highly valued in this field, since only someone who has been with a given firm for a substantial amount of time, would be able to generate viable data for the organization’s growth.
  • Forms of employment
    • Part-Time: Not recommended as BI developers require extensive company knowledge in addition to technical know-how.
    • Full-Time: Most preferred, since job security increases with experience in a data science career.
  • Famous recruiting companies
    • Rolls Royce
    • Dell
    • Amazon
    • Microsoft
    • Discover
  • Average initial salary structure
    • India: 6.5 Lakhs per annum (INR)
    • USA: 73.8k per annum (USD)

Machine Learning Scientist

Machine Learning Scientist
  • Job description
    • As described in our Machine Learning Vs Data Science blog, a machine learning engineer/ scientist is highly in demand within the data science field. He/ She is the one responsible for developing the algorithm that would train the model, which in turn will analyze the given data and produce in the form of a structured output. This role will require extensive technical knowledge and a strong background on programming with languages like R and Python.
  • Educational requirements
  • Forms of employment
    • Part-Time: Opted by many with extensive programming skills, who would prefer to freelance and share their expertise widely
    • Full-Time: Preferred by engineers who have a strong technical background and are looking to establish their data science career.
  • Famous recruiting companies
    • Hotstar
    • McAfee
    • MakeMyTrip
    • Amazon
  • Average initial salary structure
    • India: 7.2 Lakhs per annum (INR)
    • USA: 111.5k per annum (USD)

Statistician

Statistician
  • Job description
    • A statistician can be considered as the backbone for the entire data science industry since it is the statistician’s analysis and calculation that helps all the other data science members in their exploration. A statistician should apply mathematical theories and formula to obtain data that will help further the business
  • Educational requirements
    • A bachelor’s degree in Math (preferably statistics)
    • A master’s degree (Not compulsory but usually held by most statisticians and preferable)
    • PhD (Will greatly help to advance in the field)
  • Forms of employment
    • Part-Time: Mostly preferred as statistics is a stronghold for many fields and not just data science, due to which many Statisticians would prefer not to limit themselves to a single industry
    • Full-Time: Preferred by individuals with an interest to pursue a data science career.
  • Famous recruiting companies
    • Google
    • LinkedIn
    • Twitter
    • Facebook
    • Microsoft
  • Average initial salary structure
    • India: 5.5 Lakhs per annum (INR)
    • USA: 93.5k per annum (USD)

Applications Architect

Applications Architect
  • Job description
    • An Applications architect oversees the development process behind software applications or Machine Learning (ML) Algorithms, provides the necessary technical support for employees to understand the functioning of the software and creates technical documents for future use.
    • The Applications Architect acts as the perfect bridge between a Machine Learning Scientist/ Engineer and a Business Intelligence (BI) Developer. He/ She will have to possess both a technical know-how and a deep business acumen, the perfectly balanced role.
  • Educational requirements
    • A bachelor’s degree (preferably in Computer Science, Bioinformatics or Engineering)
    • A master’s degree (Not compulsory but preferable as it will help increase the technical knowledge greatly required to pursue this branch of the data science career path)
  • Forms of employment
    • Part-Time: Not preferred as Applications Architects should have a clear understanding of the business’s inner workings which may not be available to part-time employees
    • Full-Time: Preferred by individuals with an interest to excel in the data science career path.
  • Famous recruiting companies
    • Amazon
    • IBM
    • TVS
    • Wells Fargo
  • Average initial salary structure
    • India: 8.1 Lakhs per annum (INR)
    • USA: 134.5k per annum (USD)

Infrastructure Architect

Infrastructure Architect
  • Job description
    • This is primarily an IT (Information Technology) related job which requires the Architect to implement and maintain the complex computer systems and technical infrastructure. An infrastructure architect will be responsible for ICT (Information and Communication Technology) performance and security too. This is a highly popular profile that is not only restricted to data science but compulsorily required in all industries of the current corporate setup.
    • In Data Science, with the massive amounts of data that are processed, the need of an Infrastructure Architect will always be present to help maintain the integrity and safety of all systems and models.
    • Another subset of the role is the cloud infrastructure architect, who would be responsible for all cloud computing activities.
  • Educational requirements
    • A bachelor’s degree (Computer Science or Information Technology)
    • A master’s degree (Not compulsory but preferable to venture further on the data science career path)
  • Forms of employment
    • Part-Time: It is not preferred since Infrastructure Architects are the first line of defense against any safety or performance issues. So companies would prefer to have them full-time to ensure the smooth functioning of all systems.
    • Full-Time: Preferred by companies and individuals in the field.
  • Famous recruiting companies
    • Ford
    • IBM
    • Accenture
    • Infosys
  • Average initial salary structure
    • India: 9 Lakhs per annum (INR)
    • USA: 126.4k per annum (USD)

Hence, as seen above the scope of data science careers is quite high and with some careful research and the proper qualifications, you could easily start on the path of your data science career. Also, go through the top questions asked in data science interview as you prepare to step into your career.

For those who have completed their UG or PG courses and are looking for a foray into the field, the Henry Harvin Data Science Courses would be a wonderful online platform to obtain your certifications and the coveted data scientist education. Hurry up to climb up the ladder of opportunity!

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Henry Harvin® is a leading career and competency development organization with focus on value creation. We are into the business of training, skill development, assessment centres, content services and higher education. Our dream is to establish 'Henry Harvin®' in line with the vision of Mr.Henry Dunster 400 years ago which now resonates in the form of a prestigious educational institution respected worldwide.

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