Gyansetu Team 
A Ph.D. in data science equips candidates for advanced studies in the field, potentially enhancing their career prospects. However, whether pursuing one depends on personal goals and resources. For aspiring data scientists, a Ph.D. is not always essential. Here are valuable tips for Ph.D. holders aiming for a data science career. Explore data science training in Gurgaon at Gyansetu for practical skills and insights.
Emphasise the parallels between the thesis work and potential professional projects.
The data science career is hugely impacted by having composed a thesis. The students should remember that as Ph.D. holders, they have essentially completed a five-year project and were fully accountable. They also frequently give talks, presentations, and summaries of their research, which is exactly what their job involves as a data scientist. Work schemes are virtually like a whole thesis condensed into one or two quarters. Only now, they have a bunch of colleagues who will help them to figure out the difficulties. In the resume and the interviews, they should find ways to draw parallels between their work experience from their Ph.D. and the commitments summarised in the job description.
The students should Take time to practise their hard skills. They aren’t easy.
- Studying the algorithms and data structures from a lot of distinct sources is crucial for aspiring students.
- Reviewing the statistics. They should know the different regression types, values, and t-tests.
- They should know how to compute expectation values in combinatorics difficulties.
- If they are using Matlab, Fortran, etc., it’s time to make the change to Python or R. They should build fun side projects to practise their skills.
- Give the required time to learn recursive programming, and it’s a different way of thinking, so they can’t do it at night.
- Learning and working with SQL.
Interact with the tech community as much as possible.
The students should learn the language, the lingo, how people chat, and how people think. They should also learn what people value. They will sound like an alien if they have done none of this. They have to show, by doing, that they are ready to learn the vernacular.
Choose a company with an employee size that fits your needs.
Many love the fact that Twitter is a medium-sized company, and it’s big enough that anyone can learn a lot from the experts around them but small enough that it can have a big impact. For many, that’s an ideal equilibrium. The students should consider their desired mix and get lots of guidance from veterans along the way.
Finding out what skills are required for data scientists
Skills are required to differ by the corporation, and it changes over time. Besides, data scientists may imply different jobs in various companies. So first, the candidates should find out the skills required for the kind of “data scientist” they want to be. The following are the essential ones.
- Statistics
Undergraduate-level statistics course to understand methods like A/B testing and another hypothesis testing
Statistical model for data analysis
- Machine learning
- Programming
- SQL
- R and Python are the most famous languages for data scientists.
- The algorithm and data structure is good to know.
- Business analysis
- Product sense
- Good communication
Take classes and read books
One benefit of being a Ph.D. student is access to numerous free resources that are often scarce outside of academia. Years of research training also teach Ph.D. students how to effectively utilize these resources. Regardless of educational goals, entering the data science field requires comprehensive knowledge and training.
While a Ph.D. is not mandatory, it can significantly enhance skills for a data science career. Explore training opportunities with Gyansetu to gain the necessary expertise in data science.
