7 answers
Laila
Student
Fontana, California
3
Questions
Asked
663 views
How Can I Get Into Biostatistics as a CS Major?
I'm a second-year undergraduate computer science student, and I need some advice from anyone with experience finding their pathway in computer science. While I was applying to a research program, I found a passion to apply data science to biomedical research or biostatistics, and I want to delve further. My goal is not only to demonstrate my dedication to the research program. I want to cultivate my passion for data science and commitment to helping underrepresented groups, specifically Black women, through data-driven solutions.
What do you suggest as a good starting point, or any tips on how I can delve further into data science in and out of the classroom? Are there any books or websites you suggest? Are there tools and skills you strongly recommend I build up? For someone like me, who never had a strong interest in biology but wants to improve public health, how would I go about that?
I appreciate any resources or advice anyone has to offer! Thank you!
Login to comment
6 answers
Sammantha White
Pioneering
17
Answers
Arvin, California
Updated
Sammantha’s Answer
Below is a clear, structured roadmap based on what students in your exact position typically need.
---
🌱 1. Start With the Core Data Science Skills
These are the non‑negotiables — the foundation you’ll use in any biomedical or public‑health project.
🧰 Programming (Python + R)
• Python is widely used for medical analytics, especially with libraries like NumPy, Pandas, Matplotlib, and ML frameworks. GeeksForGeeks
• R is heavily used in biostatistics and public health research.
đź“Š Statistics & Machine Learning
Biomedical data science relies heavily on:
• Predictive modeling
• Statistical inference
• Data cleaning and preprocessing
• Exploratory data analysis
These are highlighted as core skills for biomedical data scientists. National Lib...
🧼 Data Cleaning & Preprocessing
Healthcare data is messy — missing values, noise, inconsistent formats.
Understanding how to clean and structure data is essential. Number Analy...
---
🧬 2. Build Biomedical Literacy (Even If Biology Isn’t Your First Love)
You don’t need to become a biologist — you need functional literacy.
According to the National Library of Medicine, biomedical data scientists need general working knowledge of:
• Basic biology
• Bioinformatics
• Clinical concepts (diagnosis, disease categories, etc.) National Lib...
How to build this without taking a ton of biology classes:
• Take Intro to Public Health or Epidemiology — these are data-heavy and accessible.
• Use beginner-friendly resources like Data Science for the Biomedical Sciences (Daniel Chen), which teaches data skills through biomedical examples. rbind.io
• Explore Introduction to Biomedical Data Science for a broad overview of biostatistics, databases, and healthcare datasets. r4stats.com
---
🧠3. Explore Data Science in Public Health & Health Equity
You mentioned wanting to help underrepresented groups, especially Black women.
That’s a powerful and needed direction.
Ways to connect data science with health equity:
• Analyze disparities in maternal health outcomes
• Study access to care, chronic disease prevalence, or environmental health impacts
• Work with community organizations that collect health data
• Join research labs focused on epidemiology or social determinants of health
Your lived perspective + technical skill = unique value in these spaces.
---
🧪 4. Get Hands-On With Real Biomedical Data
This is where your passion becomes visible to research programs.
Try working with:
• Public health datasets (CDC, NIH, WHO)
• Electronic health record (EHR) sample datasets
• Genomic or clinical trial datasets
• Kaggle medical competitions
The more real data you touch, the stronger your applications and confidence become.
---
đź“š 5. Recommended Books & Websites
Beginner-Friendly
• Data Science for the Biomedical Sciences — gentle intro using real biomedical data. rbind.io
• Introduction to Biomedical Data Science — covers biostatistics, databases, ML, and more. r4stats.com
Websites
• NumberAnalytics: Biomedical Data Science Essentials — great overview of concepts and trends. Number Analy...
• GeeksForGeeks: Medical Analysis Using Python — practical tutorials for medical data analysis. GeeksForGeeks
• NIH / NLM Core Skills Report — outlines what biomedical data scientists need to know. National Lib...
---
🛠️ 6. Tools You Should Learn
Programming & Analysis
• Python (NumPy, Pandas, Matplotlib, Scikit‑Learn)
• R (tidyverse, ggplot2, caret)
Data Tools
• SQL
• Jupyter
• BioPython or
• Tableau or Power BI (for
My number is 6616471632
---
🌱 1. Start With the Core Data Science Skills
These are the non‑negotiables — the foundation you’ll use in any biomedical or public‑health project.
🧰 Programming (Python + R)
• Python is widely used for medical analytics, especially with libraries like NumPy, Pandas, Matplotlib, and ML frameworks. GeeksForGeeks
• R is heavily used in biostatistics and public health research.
đź“Š Statistics & Machine Learning
Biomedical data science relies heavily on:
• Predictive modeling
• Statistical inference
• Data cleaning and preprocessing
• Exploratory data analysis
These are highlighted as core skills for biomedical data scientists. National Lib...
🧼 Data Cleaning & Preprocessing
Healthcare data is messy — missing values, noise, inconsistent formats.
Understanding how to clean and structure data is essential. Number Analy...
---
🧬 2. Build Biomedical Literacy (Even If Biology Isn’t Your First Love)
You don’t need to become a biologist — you need functional literacy.
According to the National Library of Medicine, biomedical data scientists need general working knowledge of:
• Basic biology
• Bioinformatics
• Clinical concepts (diagnosis, disease categories, etc.) National Lib...
How to build this without taking a ton of biology classes:
• Take Intro to Public Health or Epidemiology — these are data-heavy and accessible.
• Use beginner-friendly resources like Data Science for the Biomedical Sciences (Daniel Chen), which teaches data skills through biomedical examples. rbind.io
• Explore Introduction to Biomedical Data Science for a broad overview of biostatistics, databases, and healthcare datasets. r4stats.com
---
🧠3. Explore Data Science in Public Health & Health Equity
You mentioned wanting to help underrepresented groups, especially Black women.
That’s a powerful and needed direction.
Ways to connect data science with health equity:
• Analyze disparities in maternal health outcomes
• Study access to care, chronic disease prevalence, or environmental health impacts
• Work with community organizations that collect health data
• Join research labs focused on epidemiology or social determinants of health
Your lived perspective + technical skill = unique value in these spaces.
---
🧪 4. Get Hands-On With Real Biomedical Data
This is where your passion becomes visible to research programs.
Try working with:
• Public health datasets (CDC, NIH, WHO)
• Electronic health record (EHR) sample datasets
• Genomic or clinical trial datasets
• Kaggle medical competitions
The more real data you touch, the stronger your applications and confidence become.
---
đź“š 5. Recommended Books & Websites
Beginner-Friendly
• Data Science for the Biomedical Sciences — gentle intro using real biomedical data. rbind.io
• Introduction to Biomedical Data Science — covers biostatistics, databases, ML, and more. r4stats.com
Websites
• NumberAnalytics: Biomedical Data Science Essentials — great overview of concepts and trends. Number Analy...
• GeeksForGeeks: Medical Analysis Using Python — practical tutorials for medical data analysis. GeeksForGeeks
• NIH / NLM Core Skills Report — outlines what biomedical data scientists need to know. National Lib...
---
🛠️ 6. Tools You Should Learn
Programming & Analysis
• Python (NumPy, Pandas, Matplotlib, Scikit‑Learn)
• R (tidyverse, ggplot2, caret)
Data Tools
• SQL
• Jupyter
• BioPython or
• Tableau or Power BI (for
My number is 6616471632
I deeply appreciate the detailed advice! Having a clear roadmap is really helpful for someone like me who needs clear instructions. Despite programming for a few years and taking a few biology classes throughout my academic career, I'm still trying to grasp some concepts, so I'm glad you listed some resources and specific things to focus on. Thank you for the advice!
Laila
Ibrahim Ali
Software Developer
21
Answers
Mogadishu, Banaadir, Somalia
Updated
Ibrahim’s Answer
That’s a great question, and you’re already on a really strong path by combining computer science with an interest in health and research.
The good news is that biostatistics is actually a very natural fit for a CS major. You already have one of the hardest parts programming and problem-solving. What you need to add now is some statistics and basic biology or public health knowledge. Think of it as “layering” new skills on top of what you already know.
A good starting point is to focus on statistics and data analysis. If you can, take courses like probability, statistics, or data science. Also try to get comfortable with tools like Python or R for analyzing data, especially libraries used for data work. In biostatistics, people care a lot about understanding data, not just coding.
Outside the classroom, try to work on small projects related to health or biology. For example, you could find a public health dataset online and explore it look for patterns, build simple models, or visualize trends. This shows real interest and helps you learn faster than just classes alone.
Since you mentioned you don’t have a strong biology background, don’t worry too much. You don’t need to become a doctor. Just start with basic concepts things like how diseases spread, what clinical studies are, or how health data is collected. Even short online courses in public health can help you feel more confident.
One more idea is to look for research opportunities or internships, even small ones. Labs and professors often need students who can code and work with data, and that’s where you can stand out.
You’re in a great position because you’re combining tech with real-world impact. Keep exploring, build small projects, and stay curious you’re definitely moving in the right direction.
The good news is that biostatistics is actually a very natural fit for a CS major. You already have one of the hardest parts programming and problem-solving. What you need to add now is some statistics and basic biology or public health knowledge. Think of it as “layering” new skills on top of what you already know.
A good starting point is to focus on statistics and data analysis. If you can, take courses like probability, statistics, or data science. Also try to get comfortable with tools like Python or R for analyzing data, especially libraries used for data work. In biostatistics, people care a lot about understanding data, not just coding.
Outside the classroom, try to work on small projects related to health or biology. For example, you could find a public health dataset online and explore it look for patterns, build simple models, or visualize trends. This shows real interest and helps you learn faster than just classes alone.
Since you mentioned you don’t have a strong biology background, don’t worry too much. You don’t need to become a doctor. Just start with basic concepts things like how diseases spread, what clinical studies are, or how health data is collected. Even short online courses in public health can help you feel more confident.
One more idea is to look for research opportunities or internships, even small ones. Labs and professors often need students who can code and work with data, and that’s where you can stand out.
You’re in a great position because you’re combining tech with real-world impact. Keep exploring, build small projects, and stay curious you’re definitely moving in the right direction.
Thank you so much for the advice! I recently applied to a handful of biostatistics research programs and am trying to get a grasp on R through RStudio. I'll definitely look into resources about basic biology and find some datasets to mess with. I also declared a data science minor, and I'm trying to rearrange my electives to focus on data. Do you recommend any specific sources to find public health datasets?
Laila
Laila B
16
Answers
New York, New York
Updated
Laila’s Answer
You've received some great advice already!
Here's a bit more: consider exploring internships with pharma or biotech data teams, like those at Genentech or Amgen. Also, check out organizations like the Satcher Health Leadership Institute, which focuses on health disparities affecting Black women.
Since you're learning R, try adding tidymodels to your skills. You're doing fantastic!
Here's a bit more: consider exploring internships with pharma or biotech data teams, like those at Genentech or Amgen. Also, check out organizations like the Satcher Health Leadership Institute, which focuses on health disparities affecting Black women.
Since you're learning R, try adding tidymodels to your skills. You're doing fantastic!
Thank you so much for the advice! I'll be looking into these companies and organizations. I'll also be adding tidymodels to my R arsenal.
Laila
Ganesh Raut
1
Answer
Pune, Maharashtra, India
Updated
Ganesh’s Answer
High Demand for Data Scientists: 2026 statistics In the year of 2026, we have one of the highest need for data scientists and fresher are in a good position to step into this fertile career choice within technology. For a fresher or a newly graduated data scientist, the question arises — how can we get into this field and what types of jobs are available for freshers. We are going to take you through what kind of roles there are, the skills you should posses and how you can find your route to success in the data science realm.
The Data Science Is A Evergreen Career Until 2026.
Data science remains one of the fastest-growing domains in tech. With organizations making decisions from data, forecasting trends utilizing data, and optimizing processes based on data, companies are in becoming more dependent upon the predictions of a group like Data Scientists. As it applies to nearly every industry, such as healthcare, finance, retail or entertainment among others: this field has many opportunities for freshers.
Main Drivers for the Data Science Boom:
Global Data Explosion: As more and more data gets generated worldwide, organizations are in need of skilled professionals who can process this data and perform analysis on it.
Automation and AI: As Artificial Intelligence & Machine Learning are coming into big decisions, understanding the fundamentals of data science is a must.
Industry Diversification → Data science is not confined to tech corporations anymore. Data-driven solutions have major part of the industries such as health-care, finance and logistics.
The Data Science Is A Evergreen Career Until 2026.
Data science remains one of the fastest-growing domains in tech. With organizations making decisions from data, forecasting trends utilizing data, and optimizing processes based on data, companies are in becoming more dependent upon the predictions of a group like Data Scientists. As it applies to nearly every industry, such as healthcare, finance, retail or entertainment among others: this field has many opportunities for freshers.
Main Drivers for the Data Science Boom:
Global Data Explosion: As more and more data gets generated worldwide, organizations are in need of skilled professionals who can process this data and perform analysis on it.
Automation and AI: As Artificial Intelligence & Machine Learning are coming into big decisions, understanding the fundamentals of data science is a must.
Industry Diversification → Data science is not confined to tech corporations anymore. Data-driven solutions have major part of the industries such as health-care, finance and logistics.
Jim Loiacono
Global Technical Sales
6
Answers
Scottsdale, Arizona
Updated
Jim’s Answer
Consider reaching out to the HR departments of pharmaceutical device manufacturers and law enforcement crime labs for an internship. Let them know you're willing to offer your time and effort in exchange for valuable experience. It could be a great opportunity for both you and them!
Thank you for the advice! I'm still navigating whether I want to work in industry or academia, but I'll definitely look into this.
Laila
Sammantha White
Pioneering
17
Answers
Arvin, California
Updated
Sammantha’s Answer
https://www.careervillage.org/groups/6585/astra-foundation-inc/
That’s my group
That’s my group