Introduction
Hello everyone, my name is Gauri Kulkarni. I embarked on my academic journey in India with a clear vision and passion for the research industry. While my peers aspired to become doctors, I knew that my calling lay in the world of scientific exploration and discovery. This led me to pursue a Bachelor of Engineering in Instrumentation and Control with a major in Biomedical Engineering.
During my undergraduate years, I developed a solid understanding of engineering principles. In my final year, I had the incredible opportunity to work on a project aimed at developing a device to detect Parkinson’s disease. This experience ignited a deep interest in neurodegenerative diseases, propelling me towards a future focused on understanding and finding solutions for these conditions.
To further my education and delve deeper into the field of Biomedical Engineering, I knew that pursuing a Master’s degree was essential. I soon realized that gaining admission to reputable schools in the United States without work experience would be challenging. Determined to acquire practical skills and knowledge, I decided to work for a year in a pharmaceutical company in India. This invaluable experience provided me with hands-on exposure to a wet lab environment and allowed me to work with cutting-edge analytical lab equipment.
In 2018, I made the decision to pursue my Master’s degree in Biomedical Engineering in the United States. I was accepted into Binghamton University, where I immersed myself in my studies. With a particular focus on neurodegenerative diseases, I continued my research, eager to contribute to the growing body of knowledge and make a tangible impact in this field. I focused on detecting Alzheimer’s disease using digital biomedical engineering techniques. This research not only deepened my understanding of the field but also exposed me to various programming languages and software tools, enhancing my technical skills.
During my Master’s program, I also had the opportunity to collaborate with a PhD student. This collaboration sparked my initial interest in the field of oncology, as I witnessed the profound impact that research could have on improving cancer treatments and patient outcomes.
Upon completing my Master’s degree, I secured a job as a biomedical engineer. In this role, I primarily worked in process development, applying the engineering principles I had learned throughout my education. After a few months, I realized that my true passion lay in the research aspects of my work, particularly in the field of immuno-oncology.
Motivated by my passion for research and the desire to contribute to cutting-edge advancements in cancer treatment, I made the decision to join as a research associate in a biotechnology industry company. Here, I have been fortunate to work on groundbreaking research aimed at developing transformative cancer treatments for patients. Along the way, I have gained valuable skills, both technical and interpersonal, that have furthered my growth as a researcher.
Throughout my journey, I have come to realize that my training in engineering has been instrumental in my ability to excel in the research field. The problem-solving mindset, analytical thinking, and attention to detail that I developed during my engineering education have proven to be invaluable assets in my research endeavors.
As I look back on my experiences and the skills I have acquired, I am grateful for the opportunities that have shaped my path. With each step, my passion for research and dedication to improving patient outcomes in the field of immuno-oncology continue to drive me forward. From my beginnings in India to pursuing my passion in a foreign land, I have encountered numerous challenges along the way. But my determination and unwavering commitment to making a difference have propelled me forward.
Data Science Fellow
career options
The biotechnology and biomedical engineering fields offer a wide range of career options for individuals interested in applying science and technology to improve human health and advance medical research. These fields involve the use of biological systems, engineering principles, and technology to develop innovative solutions and products. The different careers offer opportunities for research, development, manufacturing, and consulting in various sectors such as pharmaceuticals, biotechnology companies, research institutions, and medical device companies.
The field of biotechnology and biomedical engineering is vast, with many diverse career paths. A few options have been described below, but these only encompass some career paths.
Data Science Fellow
skills
What are the main hard skills you use on a daily basis in your current job?
Aseptic techniques in the biotechnology industry are essential for maintaining the sterility and integrity of biopharmaceutical products. These techniques involve creating a sterile environment, ensuring personnel are properly trained, sterilizing equipment, and performing aseptic manipulations. Regular monitoring and validation are also crucial to ensure the effectiveness of these techniques. By implementing aseptic techniques, biotechnology companies can prevent contamination and ensure the quality and safety of their products, meeting regulatory requirements and maintaining product integrity.
SQL is essential for querying databases and extracting the necessary data for analysis. It's the language of data manipulation and is crucial in any data-driven role. I honed this skill by working on college and work projects that required efficient data retrieval and manipulation.
Git is crucial for managing code versions and collaborating effectively with team members. I use Git daily to track changes, manage simultaneous changes, and ensure seamless integration of new features. This tool is indispensable for maintaining code integrity and streamlining workflows.
Data analysis skills are crucial in biotechnology and biomedical engineering, allowing for interpreting and extracting insights from complex datasets. Proficiency in statistical analysis, knowledge of data analysis techniques, and familiarity with software and statistical packages commonly used in these fields are essential for effective data analysis.
What are the main soft skills you use on a daily basis in your current job?
Explaining complex insights to different shareholders with varying levels of technical knowledge is an art. I have learned that no matter how brilliant your analysis, it will be useless if not communicated effectively.
The ability to adapt to new tools, technologies, market conditions and business needs is essential in my role. It's like being a chameleon, always changing colors based on the environment.
The ability to work cross-functionally with multiple departments and teams is very crucial in a data science focused role. I routinely work with developers, traders, quantitative strategists, accounting and administration to ensure smooth operations and manage risk.
Pratyush
’s personal path
Tell us about your personal journey in
Data Science Fellow
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I initially came to NYC with a clear goal: to become an investment banker. The allure of Wall Street was hard to resist, and I chose the NYU Stern School of Business to pursue my ambition. However, midway through my undergraduate studies, I realized that the world of banking and consulting wasn't the right fit for me. It felt too constrained, lacking the creativity and analytical depth I was craving.
That’s when I discovered the fascinating world of data science and statistics. This pivot was like opening a door to a room full of endless possibilities, where my love for problem-solving could flourish and align with my endeavors in programming projects when younger. I changed my course’s concentration to Data Science and began stacking my internships to gain as much experience as possible in this new field. I immersed myself in coursework and on campus organizations which exposed me to the fundamentals, talking to industry experts and making specialized projects.
My first job out of college was with Natera, a biotech company, where I delved into analytics and learned the ropes of extracting meaningful insights from large datasets. From there, my journey took me to Citibank, where I worked on data engineering and development. This role was like being a behind-the-scenes conductor, ensuring that all the data flowed smoothly and efficiently. It was here that I became adept at managing complex and intricate problems.
Now, as a Trading Operations Analyst, I find myself in a unique position that blends data science, software development, and financial operations. Each day is a new adventure, filled with challenges that require a mix of technical skills and creative thinking. Whether it’s analyzing operational data to extract efficiencies and remove bottlenecks, automating trading processes or managing risk, my job constantly introduces me to new technologies and methodologies and allows me to continuously learn and grow my Python and SQL skills.
Looking back, every step of my career path has been about exploration and growth. I’ve learned to embrace change and not be afraid to seek out new opportunities. It hasn’t been linear, strictly premeditated, or straightforward, but it has been incredibly rewarding trying many different things and seeing what sticks. I cannot really predict what my career will look like moving forward, but I can ensure that you will find me still taking risks, learning and never regretting failure.
What would you tell your younger you regarding building your current career?
I’d say “Don’t stress so much about finding the ‘perfect’ career path. It’s okay to change your mind and explore different fields, roles and careers. Focus on giving your best in whatever you are doing now and trust your gut. You didn’t believe time travel was possible and here I am here talking to you!”
Final thoughts & tips
Remember that every career path is unique. Don’t be afraid to pivot if something doesn’t feel right or something more exciting comes along. If your career doesn’t follow a traditional path, doesn’t mean it’s the wrong one.
At the end of the day, it is what you are spending most of your time doing, ensure that it makes you get out of bed. Find some joy in everything you do! Be patient, stay curious, and keep learning.
Resources to dig in more
Simply Statistics
Run by three biostatistics professors, this blog explores the use of statistics in big data across various fields. It’s an essential resource for anyone looking to understand the statistical foundations of data science.
StatQuest with Josh Starmer
StatQuest is a Youtube channel that breaks down complex concepts in Statistics, Machine Learning into simple, easy-to-follow videos. Josh Starmer has a knack for using clear visuals to complement their explanations, making this an excellent resource for visual learners!
Data Skeptic Podcast
The Data Skeptic podcast explores data science, statistics, machine learning, and artificial intelligence in a way that is accessible to both experts and beginners. Each episode focuses on a particular topic and features interviews with industry experts, making it a great resource for learning on the go.
Kaggle Discussions
Kaggle Discussions is a reddit like platform by Kaggle (a Data Science projects and competitions website). Discussions has a thriving community where users share insights, discuss challenges and learn from each other; it is a goldmine of knowledge with threads ranging from beginner tips to advanced model boosting techniques.
