Jennifer Niemann, M.S.

Ms. Niemann graduated from our MS Biostatistics program in fall 2019. She is currently working as a Research Associate at the University of Miami Rosenstiel School of Marine, Atmospheric, & Earth Science.

What skills, abilities, and personal attributes are essential to success in your field?

Basic stats, data cleaning/manipulation, data visualization, R, and SAS are all skills I use every day. In addition to these statistical and data science related skills, time and project management; ability to research, think critically, and problem solve; and communication (written and verbal) are the most used skills for my job.

What do you enjoy the most about the work you do?

I get to research and communicate with some of the most brilliant climate scientists. I am also involved with current Master’s and PhD students in our Climate Risks & Preparedness research group, so I am constantly learning about others’ current research projects, which is always interesting. I get to work on so many fascinating projects dealing with climate change impacts, adaptation efforts, and climate and racial justice initiatives.  

What do you wish you had known when you were starting out in your career?

(This is something I wish I had assured of at the start of my master’s program.) Statistics and data science skills are incredibly transferable! Whether you end up as a biostatistician or some other type of data-wrangler, the skills you learn while getting your Biostats degree will set you up for success. These are such sought after skills, and even if the research you end up working on is non-medically related, you will be able to apply them with ease. I never expected to end up in a career related to climate science, but I am fully embracing and loving the unexpected.

Can you explain your current job placement?

I conduct statistical analyses while researching community climate change risk adaptation methods and perceptions. My research is usually focused on 1) aspects of migration as a result of climate change impacts or 2) floodplain development and management, both through the lens of climate and racial justice.

What aspect of your biostatistics program at the KUMC did you enjoy the most of find to be the most helpful in preparing for your next steps?

My favorite part of the program was the small class sizes. This really allowed for a rich learning environment—one where there was time and space for every student to understand the material and ask questions. It also contributed to the fact that the other people in my year became really great friends during that time. I’m still thankful for the friendships I made at KUMC!

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Jiawei Duan, Ph.D.  

Dr. Duan graduated from our Ph.D. Biostatistics program in fall 2019. He is currently working as a Senior Principal Biostatistician at Novartis Pharmaceuticals Corporation.

Tell us a little bit about your career path and what led you to the role you are in today.

While pursuing the Ph.D. degree in Biostatistics at KUMC, I had the career goal of being a biostatistician in the pharmaceutical industry because I enjoy exploring clinical trial design and data with my knowledge in statistics to help deliver new treatment to patients. It is my passion for clinical trial that led me to my current role and drives me to dig into the field of pharmaceutical biostatistics.

What skills, abilities, and personal attributes are essential to success in your field?

In the pharmaceutical industry, I think there are three types of skills that are important to the success of a biostatistician: communication skills, statistical knowledge, and leadership skills. Communication skill enables a biostatistician to effectively express the idea and interpret statistical knowledge in a way that others with varied background can understand. Good understanding of statistical knowledge is essential to designing clinical trials and understanding the data. And leadership skills is the sense of influencing others to achieve a common goal and it is dependent on both effective communication and strong statistical knowledge.

What is your favorite part of being a biostatistician?

My favorite part of being a biostatistician is to collaborate with my colleagues during the conduct of a clinical trial. I enjoy participating in team's discussion and providing statistical expertise on how the study should be designed to answer the scientific question of interest. I also enjoy applying statistical knowledge and helping the team understand and interpret the data collected in the clinical trial.

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Lucas Braga, M.S.

Mr. Braga graduated in fall 2020 from the Master of Science in Applied Statistics, Analytics & Data Science program with an emphasis in Data Science. Mr. Braga is currently a Data Science Manager at Delivery Hero. He manages a team of two data scientists and works for a large tech company in Europe, where their role is to develop machine learning models and anomaly detection models to prevent fraud in online payments and cash payments.

Tell us a little bit about your career path and what led you to the role you are in today.

In 2014, one year after I finished my Bachelor's in Business Administration, while working as Business Operations Coordinator, I discovered that with Analytics I could make much better business decisions and achieve much more results. So in 2015, I started to work full time with data analytics, first as Business Analyst for DHL in Frankfurt, Germany. Then I had more senior roles after a couple of years. Then in 2018 I started my Master's degree with KUMC in Statistics, Analytics and Data Science. And in 2019 I started to work in a tech company in Berlin, Germany, first as a Senior Data Analyst, and after 1 year, in 2020, the year that I graduated, I started to work as a Senior Data Scientist. Now it's 2023, I've been recently promoted to Data Science Manager.

What lessons did you learn in earlier roles that help you today?

It's important to keep up with technology, or else, you won't be able to grow much in this career. That means, to be aware of the trends in the market and work with the languages and tools that are in most demand. Please note that what's in demand is not necessarily the same as what's the trend. What's in demand means what's most used by the market, so for example, for Data Science, in terms of programming language that would be python.

What do you enjoy the most about the work you do?

I like the feeling that I have when I'm developing a product, it feels like I'm building something, constructing something, either a business or someone will use it.

What do you wish you had known when you were starting out in your career?

I wish I knew that anything you can do with excel can also be done with python, and python is not so complicated, if you've learned VBA or any other programming language, it's a smooth transition. I also wish I knew of any startups that were willing to take in people without experience in data science, in their early career, and pay them as junior, but guide and mentor them to become an experienced professional. Since I didn't know any, my strategy was to learn by myself and to always apply my new learnings at the current job that I had. I think that's also a good way to go.

What aspect of or experience in your biostatistics program at the KUMC did you enjoy the most or find to be the most helpful in preparing for your next steps?

I believe the python programming classes, the classes about machine learning algorithms, combined with some amazing people that I've met there, were the most enjoyable and the most helpful.

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Alex Karanevich, Ph.D.

Mr. Karanevich graduated from our Ph.D. Biostatistics program in fall 2017. He is currently working as a Senior Biostatistician at EMB Statistical Solutions.

What skills, abilities, and personal attributes are essential to success in your field?

Understanding statistics is certainly important: the statisticians on a clinical trial needs to ensure the trial is correctly designed to answer the clinical question(s), and that it is capturing all the necessary and relevant data. Other technical skills including programming the standardized datasets and outputs (the pharmaceutical industry is still predominantly SAS), performing the statistical analyses, running simulations, etc. are all important too. Soft skills, especially organization and communication with statisticians and non-statisticians, are absolutely critical as well. As your project load ramps up, simply keeping track of emails, meetings, and timelines across projects can be a challenge.

What do you enjoy the most about the work you do?

I get to work on a very diverse collection of projects. My typical projects are later-phase clinical trials, but I have worked on early-phase and post-marketing trials as well. I’ve also been involved in trials that span a huge variety disease indications: oncology, neurology and ophthalmology, to name a few. But the variety doesn’t stop there – I also get to work on all sorts of unique consulting projects, which can include salvaging trials that have gone awry, exploring novel statistical methods, proposing adaptive designs, and even sometimes analyzing animal studies!

What do you wish you had known when you were starting out in your career?

That you can never be too organized. Juggling ten or more projects with timelines that are measured anywhere from a few months to several years can become a challenge to keep track of. I’ve found OneNote and Outlook to be invaluable tools to for organization.

Is there something that surprised you about the role when you first started?

The statistical simplicity of many trials. In academia, it seemed like every trial had some sort of statistical novelty: adaptive designs, unique analyses, augmentation from historical data, and so on. But in industry, it is not uncommon to see a simple 1:1 randomization of treatment vs. control that simply uses a t-test at the very end. There is a lot of opportunity to leverage more advanced methodology.

What aspect of your biostatistics program at the KUMC did you enjoy the most of find to be the most helpful in preparing for your next steps?

My fondest experience in the biostatistics program was an incredibly organic collaborative research project that was quickly published in the Journal of the American Statistician. I was trying to optimize patient allocation in a particular Bayesian design, and the software I was using required me to manually test dozens of cases to figure out where this optimal split was. I knew there had to be a better way – so I collaborated with fellow graduate students Stefan Graw and Richard Meier to find a solution. Working together, we rapidly developed an R package, a Shiny interface, and a paper, which we presented at a local conference. The keynote speaker at that conference later approached us, informed us he was the editor of the Journal of the American Statistician, and suggested we submit there. So, we did, and it was published soon after. From start to finish, the whole process was wonderfully smooth and enjoyable, and it is a very fond memory of mine.