Data Science is an amalgamation of maths, computing, statistics and people. Here is a list of skills that you’ll need to hone for a career in Data Science:
- A good hold in Statistics, Mathematics, and Machine learning
- Fluency in a coding language, probably R or Python
- An understanding of databases
- Experience with big data tools like Hadoop, Spark, and MapReduce
- Experience with data munging, visualization, and reporting tools
Further skill development will take place through competitions, pet projects, internships, boot camps and by meeting fellow data scientists.
Below is the typical trajectory followed in a Data Science career, along with the roles and responsibilities involved:
Step #1: Executive
Executives might be MBA graduates or BBA freshers. They are typically involved in the making of CRM reports, MIS (Management Information System) and DQA (Data Quality Assessment).
Step #2: Analyst
Analysts are involved in product tech support, data munging, sales lead, CRM, data visualization, advanced statistics, MDM corrections and carry out all the roles and responsibilities related to the same.
Step #3: Business Analyst
Most people confuse business analysts with analysts, but the former is 1 step above. Hence, their concerned domains also differ and include product/ project SDLC, programming logic and solutions, vendor coordination, MDM & logics, and business processes.
Step #4: Data Architect
The role of Data Architects generally revolve around data warehousing, data architecture development, data modelling, ETL working, data cleaning, and elastic working and functionalities.
Step #5: Chief Data Officer/ Data Scientist
The CDO works with advanced data algorithms, advanced predictive algorithms, big data processing, NoSQL, and ETL logic. Their primary task is also to innovate and hence, they are the creators.