Two women on different sides of world who had never participated in a Kaggle competition came together as a team to compete in the WiDS Datathon 2022—leading to new skills, confidence, and a lasting friendship. The datathon goal was to analyze the energy efficiency of buildings. Participants analyzed regional differences in building energy efficiency, creating models to predict building energy consumption, an important first step in understanding how to maximize energy efficiency.
We asked Pravallika Myneni and Anissa Amziani to tell us more about themselves and the experience of working together during the datathon competition.
Tell us about your experience working together on the datathon.
We met through the Kaggle discussion board. Initially we were a team of four, but two team members dropped out. In the last week of the datathon, the two of us decided to team up and participate. It was our first Kaggle competition and Anissa’s first datathon. We are from different time zones which made it extra hard. We used Google Meet and Slack for communication. Each time we had a meeting, we discussed the progress and next potential steps. Coming from different levels of experience definitely helped us. We are proud of our team data_divas and what we have learned. Pravallika and I quickly clicked, and we are still learning and attending workshops together as well as meeting regularly to discuss our progress.
Tell us about your background.
Pravallika Myeni: I am from Andhra Pradesh, India. Growing up I loved math and solving puzzles with my mom. Logic helped me win prizes in math Olympiads, and soon became the inspiration for choosing my career. I wrote my first program in 9th grade and loved being able to delegate problem solving to machines. This opened new horizons for me. I decided to pursue a B. Tech in Computer Science and Engineering. Apart from academia, I enjoy meeting people, working on my personal projects, and taking part in hackathons. So far, I have participated in around 50 hackathons/datathons. I joined Lisbon Data Science Starter’s Academy to advance my skills in data science.
Anissa Amziani: I was born and raised in Algeria. I moved to the US at the end of 2014. I earned a Master of Science in Operations Research Engineering from USTHB, Algeria and a MS in Financial Engineering from Temple University in Philadelphia. I always loved mathematics and solving challenging problems. I love cooking, biking, travelling, and playing Scrabble!
How did you get interested in data science?
Pravallika: My interest in data science started when I took the course “Database Management Systems” as an undergrad. I think the most fascinating thing about the field of data science is its interdisciplinary approach. During the pandemic lockdown, I started various hobbies and began exploring the world of data and participating in international hackathons/datathons. My research work, internships, and taking part in events organized by organizations like DataKind helped me to understand the importance and impact of data science.
Anissa: After leaving my previous company, I thought about what am I passionate about and what drives my curiosity. After many months reflecting on this, I realized that what I really like is combining my love for math, statistics, and programming with Python and applying it to real world problems. Last year, I participated in my first hackathon with the goal of developing solutions to mitigate climate change effects on Florida’s coastal regions. From then on, my interest in data science grew tremendously and I have been enjoying diving deeper into the field.
What are you currently working on?
Pravallika: I am currently working as a machine learning intern at CURVEX, applying data science to brain activity (electroencephalograms). I have been participating in the World Data League using data science to solve challenges related to UN SDGs. In Fall 2022, I will be starting my master’s degree in AI. In the meanwhile, I am taking part in a “66 days of data” challenge to enhance my data science skills.
Anissa: I am working on learning the fundamentals of OOP with Python so I can efficiently build machine learning models. I also developed a fondness for hackathons/ datathons because they are an opportunity to meet new people and learn together. I find learning more enjoyable that way and also I pick up on things faster when I work with a team. I am also a member of Women in Data, an organization that offers career development programs such as portfolio building, mentorship, and coaching programs.
How did you first discover WiDS?
Pravallika: I got to know about WiDS through a LinkedIn post. The fact that WiDS is focused on encouraging women to level up their data science skills by solving a social impact challenge inspired me to participate in the challenge. The support offered in workshops is super helpful. The WiDS datathon offered me a perfect platform to learn, apply and improve my data science skills, find a wonderful teammate and network with some amazing women in data science.
Anissa: I discovered WiDS through LinkedIn and Kaggle. I was inspired by the supportive community of women from all backgrounds and all levels. I learned a tremendous amount from this community, ranging from technical knowledge to gaining confidence that I can advance in my career and learning journey, and I am not alone in this endeavor. Honestly, the datathon was so well organized that it made me feel as if I had already participated in a datathon. I attended most of the workshops and I learned a lot from each one of them.
Have you been involved with WiDS since that first experience?
Pravallika: After the WiDS datathon, I attended the WiDS conference, and workshops. At WiDS, I had the chance to meet some wonderful women. It was inspiring to meet women from different backgrounds and share our experiences. WiDS 2022 was a great experience for me, and I look forward to taking part in WiDS 2023.
Anissa: Since the end of the datathon, I attended the WiDS global conference on March 7th where I learned a lot about different topics related to data science and women in data science. I also joined the WiDS Chicago local chapter and connected with a lot of inspiring women.
How has WiDS made an impact on your life and/or work?
Pravallika: WiDS had an immense impact on me. Through the WiDS datathon, I gained confidence in my data science skills and through the WiDS conference I learned so much from the insightful talks and found some great teammates for future collaboration.
Anissa: WiDS impacted me tremendously. I acquired confidence through participating in the datathon, I acquired new skills from attending the workshops and I made connections through it all and I got to know my friend and “learning buddy” Prava.
What comes next for you? And what are your hopes for women in data science in the future?
Pravallika: I plan to constantly learn and apply my skills to explore the applications of data science in several domains. I will also continue to take part in data science challenges. I hope for women in data science to share their stories and inspire many others to pursue careers in data science.
Anissa: I am pursuing this newly discovered passion for data science and hope to land a position from which I can learn and apply the knowledge I have acquired so far. My hope for women in data science is to keep inspiring us and pave the path for new generations of girls around the world to consider this field, fight imposter syndrome and keep fighting for a better world.