{"id":115687,"date":"2026-02-11T09:24:26","date_gmt":"2026-02-11T03:54:26","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/pharma-to-data-science-journey\/"},"modified":"2026-02-11T09:00:24","modified_gmt":"2026-02-11T03:30:24","slug":"pharma-to-data-science-journey","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/pharma-to-data-science-journey\/","title":{"rendered":"From Molecules to Models: A Pharma Scientist\u2019s Data Journey"},"content":{"rendered":"\n

Switching careers is rarely a straight or comfortable decision. When it comes after nearly a decade in a highly specialized scientific field and without external encouragement, the challenge becomes even greater. Saladi Venkateswara Rao\u2019s journey from pharmaceutical research to data science is a story shaped by self-belief, persistence, and the courage to act on a long-standing passion, even when the odds and opinions were not in his favor.<\/p>\n\n\n\n

\u201cI didn\u2019t get any support from anyone, and I completely motivated myself to do this.\u201d<\/p>\n\n\n\n

Born in Kakinada city, Andhra Pradesh state in India, Saladi Venkateswara Rao has spent the last ten years working as an Associate Scientist in the pharmaceutical industry in Bangalore. His work focused on chemical research aimed at preparing innovative cancer drugs, a role that demanded precision, analytical thinking, and consistency. While his career appeared stable and well-defined, another interest continued to surface alongside his professional growth.<\/p>\n\n\n\n

\u201cI often realised my interest was towards technology and data, and decided to go with this path.\u201d<\/p>\n\n\n\n

That interest was not something new. It had been present much earlier in his academic life.<\/p>\n\n\n\n

An Early Interest Rediscovered <\/strong><\/h2>\n\n\n\n

\u201cDuring my Higher Secondary Education time, I was more interested in statistics and technology, however due to financial burdens, I moved towards chemistry and chemical research.\u201d<\/p>\n\n\n\n

That decision shaped his academic journey, beginning with a B.Sc in Chemistry from Pondicherry University and followed by an M.Sc in Organic Chemistry from Andhra University. Over time, this path led him into pharmaceutical research, where he built close to a decade of experience. Still, his inclination toward data and technology never faded.<\/p>\n\n\n\n

\u201cI am most interested in playing with data around the world in all aspects and am interested in working on innovative things.\u201d<\/p>\n\n\n\n

When Discouragement Did Not Decide the Outcome<\/strong><\/h3>\n\n\n\n

The decision to transition into data science was met with mixed reactions from people around him.<\/p>\n\n\n\n

\u201cIt\u2019s like mixed people, some of the people discouraged me from going, some people were in a neutral state, but I analyzed myself without considering others\u2019 negative thoughts, and I decided not to give up.\u201d<\/p>\n\n\n\n

With little external encouragement, Rao relied entirely on self-assessment and internal motivation. He explored different learning paths, connected with previous students, and researched programs that aligned with his goals. <\/p>\n\n\n\n

\u201cI didn\u2019t get any support from anyone, and I completely motivated myself to do this.\u201d<\/p>\n\n\n\n

After researching programs, interacting with alumni, and understanding the curriculum, he enrolled in the Post Graduate Program in Data Science with Generative AI<\/a> offered by the McCombs School of Business at The University of Texas at Austin.\u00a0\u00a0<\/p>\n\n\n\n

Late Nights, Tight Timelines, and Continuous Learning<\/strong><\/h2>\n\n\n\n

Balancing full-time work with an intensive learning program required sustained effort and discipline.<\/p>\n\n\n\n

\u201cIt\u2019s been a great experience, but more efforts were required from my end to achieve my goals, even sometimes completing tasks in a few hours without preparation.\u201d<\/p>\n\n\n\n

Through the program, Rao developed strong technical capabilities across Python, R, SQL, data visualization, machine learning, statistical analysis, and data wrangling. He also worked extensively on exploratory data analysis, automation, data modeling, and implementation.<\/p>\n\n\n\n

\u201cMostly, I learned Python, EDA, automation, data modelling, and implementation.\u201d<\/p>\n\n\n\n

Beyond technical skills, the experience contributed significantly to his personal development.<\/p>\n\n\n\n

\u201cIn intangible ways, I developed critical thinking, collaboration, communication, time management, and adaptability.\u201d<\/p>\n\n\n\n

Building Confidence Through Hands-On Experience<\/strong><\/h2>\n\n\n\n

Practical exposure played a major role in strengthening Rao\u2019s confidence in data science. One defining experience involved completing a challenging end-to-end project.<\/p>\n\n\n\n

\u201cA standout moment from my learning journey might be when I successfully completed a challenging project, such as building a machine learning model from scratch\u2014the process of overcoming obstacles like data cleaning and model optimization would have been rewarding.\u201d<\/p>\n\n\n\n

Mentorship and peer interaction also supported his learning journey.<\/p>\n\n\n\n

\u201cOne example of a valuable connection could be a mentor who guided me through complex topics in my data science program.\u201d<\/p>\n\n\n\n

Applying Data Science in the Real World<\/strong><\/h2>\n\n\n\n

Rao is now actively exploring how to apply data science within his current role to improve efficiency and reduce operational costs.<\/p>\n\n\n\n

\u201cI don\u2019t have any idea right now, but I am trying my best to apply my skills in my current job role to make things easier and decrease time and cost effectively.\u201d<\/p>\n\n\n\n

While he continues to practice advanced coding and cloud-based automation, his broader understanding of technology has evolved.<\/p>\n\n\n\n

\u201cI may not know all the technology, but I learned how the world is growing with technology.\u201d<\/p>\n\n\n\n

Beyond career growth, the learning journey brought a shift in mindset and daily habits.<\/p>\n\n\n\n

\u201cBefore this, most of the time I wasted in my dreams; however, after doing this, I now manage my time fully without wasting it.\u201d<\/p>\n\n\n\n

This transformation became one of the most meaningful outcomes of the program, influencing how he approaches both professional and personal goals.<\/p>\n\n\n\n

A Mindset Shift Toward Discipline and Growth <\/strong><\/h2>\n\n\n\n

Beyond technical skills, the program brought a significant shift in mindset. Rao reflects that earlier, he often spent time dreaming rather than executing. The structured learning environment helped him become more disciplined and focused.<\/p>\n\n\n\n

\u201cNow, I manage my time effectively and work toward my goals with clarity,\u201d he notes. <\/p>\n\n\n\n

This transformation has become one of the most valuable outcomes of his learning experience.<\/p>\n\n\n\n

Looking Ahead: Growth, Leadership, and Impact<\/strong><\/h2>\n\n\n\n

Rao\u2019s long-term vision is focused on advancement and leadership within data science.<\/p>\n\n\n\n

\u201cMy goal is to advance into an advanced role in data science, with specialisation and leadership opportunities.\u201d<\/p>\n\n\n\n

He hopes to combine his scientific background with data-driven insights to create value across industries and contribute to innovation-led growth.<\/p>\n\n\n\n

For others considering a similar transition, his advice is rooted in experience.<\/p>\n\n\n\n

\u201cI would advise others to set career goals, choose the right program, stay committed, and balance learning with real-world applications.\u201d<\/p>\n\n\n\n

Saladi Venkateswara Rao\u2019s journey reflects the power of self-belief and persistence. By choosing to trust his instincts and invest in continuous learning, he has reshaped his career path and positioned himself for meaningful impact in the data science and AI-driven world. <\/p>\n","protected":false},"excerpt":{"rendered":"

From lab experiments to AI models, discover a pharma scientist\u2019s journey into data, analytics, and modern drug 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