Carpe Datum

Psychology & Research: Holds degrees in Psychology and Criminology, with research experience in eating habits, social media addiction, and translating data into actionable insights. Freelance Researcher: Currently works as a freelance researcher with interests in health, clinical, and sport psychology. Volunteer Work: Actively volunteers for organizations related to psychology and youth development. Women in Data Science: Co-ambassador for Trinidad and Tobago, promoting data science among women.

Inside the Northwestern Prison Education Program: Mena shares her role as a volunteer, what it’s like teaching inside correctional facilities, and how data could help evaluate or improve such programs.Founding Women in Statistics at Northwestern: The story behind launching the group, how it created community, and how it led to her regional ambassador role with Women in Data Science (WiDS) Chicago.Why Statistics?: A personal look into what drew her to pursue a Ph.D. in statistics especially in relation to social impact, health, and criminology.Accessible Data Education: Reflections on teaching statistics and data visualization to visually impaired students key takeaways on making data truly inclusive.Data Science with Heart: How Mena connects data science to real-world issues, community service, and education and why those connections matter now more than ever.Link to WiDS Chicago: https://widschicago.org/

Building Professional Relationships: Insights into how Maheen has built strong professional connections, leading to numerous recommendations on LinkedIn, and tips for fostering meaningful professional relationships. Volunteering in Data Science: Advice for data professionals on leveraging their AI/ML expertise in volunteer work, making a meaningful impact, and transitioning into the volunteer space effectively. Navigating Challenges in Healthcare Data: Lessons learned from working on statistical modeling for health insurance clients, strategies for addressing privacy concerns, and training teams to apply machine learning to real-world problems. Mentorship and Impactful Projects: Highlights of the most impactful AI/ML project Maheen has worked on, and strategies she employs during Topmate meetings to mentor and guide others in the fast-evolving AI/ML field.

Balancing Multiple Projects: Discusses strategies for managing excitement and challenges in multiple tech initiatives.Importance of Digital Presence: Emphasizes the value of having an interactive portfolio and advice on building one.Excelling in Academics and Tech: Tips on staying focused and motivated while balancing a demanding academic schedule with tech fellowships.Diverse Internship Experiences: Insights on how various internships have shaped perspectives on the tech industry.Website: https://red-dune-0cd91cf0f.4.azurestaticapps.net/#home

- Statistics in Community Services and Education: Discuss the application of statistical principles in optimizing local garden projects, enhancing public health initiatives, and improving educational programs at universities like UC Berkeley. - Statistics and Personal Growth: Explore how statistical methods can offer insights into personal growth stories, such as those discussed in Soyoung’s Medium articles on career transitions. - Data-Driven Business Strategy: Review how Soyoung’s experiences at companies like Walmart, Honeywell, Abercrombie & Fitch, and Foot Locker have influenced her approach to integrating data insights into strategic decision-making.- Engagement with Leading Voices: Consider impactful questions Soyoung might ask industry leaders like Allie K. Miller and Carly Taylor, and discuss the value she finds in coffee chats and professional networking.

Use of Newsletters: Discuss how following the newsletters ‘Hiring For Tech’ and ‘Artificial Intelligence’ has influenced Riya's approach to data science projects and interview preparation. Returning to Microsoft: Explore Riya’s experience taking a break from Microsoft to go back to school, how it changed her perspective, and the new skills or lessons she brought back. Speaking Engagements: Share insights from Riya’s recent speaking engagements, including her experiences at the Women in Data Science conference and the Olympic Data Party, and how these events contributed to the open-source community.

Research Impact: Insights into Vaibhava's research on knowledge graphs, machine intelligence, IoT, and stock price forecasting, including challenges and rewards in transforming research into publications. Community Engagement: Experiences and impact of roles as an ambassador for Women in Data Science, Pie and AI, and Adobe, and strategies for balancing tech education promotion with community connections. Integration of Skills: How diverse coursework in machine learning, NLP, data manipulation, and time series analysis is applied to current projects and research, and the influence of specific courses or concepts on problem-solving. Internship Experience: How various internships in AI and data science have shaped Vaibhava's problem-solving approach and the balance between learning from different environments and contributing effectively to projects. LinkedIn Success: Strategies for gaining a large following and becoming a top AI voice on LinkedIn.

Computational Humor and Context: Role of context in pun interpretation by language models and the impact of language ambiguity on pun recognition. Irony Detection in Tweets: Distinguishing types of irony (e.g., sarcasm) in tweets and the challenges of detecting irony in short, informal texts. AI in Enterprise Solutions: Evolution of AI and Machine Learning roles in enterprise solutions over the years based on Madiha's career progression. Inclusive Learning Environments: Influence of experiences in student support roles on creating inclusive learning environments in technical fields.

Inclusion Impact: A story of how Malvika’s efforts in promoting inclusion made a difference, and trends or innovations in urban data systems likely to impact city planning and development.ChatGPT in Data Analysis: Techniques for using ChatGPT to summarize large datasets or lengthy text, common pitfalls, and the limitations of LLMs in transforming data formats.Leadership Development: Influence of past leadership roles (football captain, event coordinator) on Malvika’s approach to leading projects at Carnegie Mellon and in her current role.Staying Updated in AI: How Malvika keeps up with AI developments, incorporates insights into podcast discussions, and future AI topics of interest, particularly in areas intersecting with human experiences like dating.AI is Not Taking Your Job podcast: https://open.spotify.com/show/1qUPErphWKUg16rsVko9PP?si=ba768ac0248f4eed

Diverse Background and Leadership: Impact of university roles and extracurricular activities on managing technical projects.Engaging Different Age Groups: Tailoring complex STEM ideas for various audiences, combining experiences as a team manager and council member.Women in STEM Podcast: Inspiration behind the podcast, evolution of the vision, and surprising insights from high-profile interviews.Challenges in Digital Solutions: Experiences optimizing Tanzu Kubernetes solutions for scalability and reliability at VMware.Women in STEM podcast: https://open.spotify.com/show/4pJNT1DLx3EddXfnVuisEj?si=202c8362400a4aee

Transition from Corporate to Academic Setting: Navigating the shift from Wells Fargo to Cornell and the transferable skills. Diverse Data Projects: Insights from analyzing data in mental health, gaming, and accessibility, and lessons learned. Writing for Reinvented Magazine: Trending tech topics and their influence on marketing data analysis at Cornell. Handling Unemployment: Staying motivated during unemployment through blogging, coding, and certifications, with advice for others.

STEM Education Impact: Lydia's experience as an MIT instructor in Barcelona. The transformative power of STEM education in communities. Advice for young women exploring tech and data science. Interdisciplinary Research: Lydia’s research on the connection between music, animals, and human well-being. Encouragement for high school students to explore interdisciplinary research. ML Summer Analyst Success: Lydia’s approach to saving 1,000 hours and increasing bids by $100 million. Key skills and mindset for making a significant impact. Data Science in Industry: Transition from IBM to Visa and how previous projects in automotive and supply chain influence her work in fraud detection at Visa.

Journey in Engineering: Discussion of Maheen's path to becoming a gold medalist in engineering, her involvement in Young Inventor programs, and how these experiences shaped her career. Diverse Experiences in STEM: Exploration of Maheen’s roles as a science demonstrator, ambassador for Women in Data Science, Women Engineers, and her involvement in initiatives like Coke Studio. Current Role and Future Goals: Insights into Maheen’s current role as a SMART trainee at ANDRITZ Pulp and Paper, her next steps, and the valuable lessons she's applying from previous trainee experiences. Leadership and Advocacy: Highlighting Maheen’s work with WinSci Pakistan, including success stories from her awareness campaigns and workshops, and advice for young girls in STEM. WinSci Pakistan: https://instagram.com/winsci.pak?igshid=YmMyMTA2M2Y=

The STEM Stitch, a non-profit Katie founded, aims to provide STEM resources to students in rural areas. Intersection of computer science and domestic violence advocacy Importance of STEM education in rural communities Youth empowerment and community service Balancing passion projects with academic pursuits

Transitioning to Tech: The Data Science Bootcamp she took and Data Science Portfolio Overcoming Burnout: Acknowledge burnout, take breaks, reassess goals, and seek support. Data Science Projects: WWPS: Used NLP to analyze presidential speeches and Airbnb Superhost - analyzed data to identify factors influencing Superhost status

Online Learning - Align courses with goals, bridge theory & practice, be consistent & participate. Udacity Nanodegree - Demanding & rewarding, online flexibility + structured learning. Soft Skills for Data - Soft skills connect data to results (communication & empathy). Leader vs. Follower - Value in both! Lead = vision, Follow = mentorship & growth. AI & Data Science for K-12 - Real-world applications, engaging activities to spark curiosity. Reading, Writing & Dreams - Platform connecting tech & mentorship (or) book on human element in tech.

Data Science Career: Climbed the ladder from intern to senior data scientist at Intuit AI, designing models for various uses. Enjoys continuous learning and driving positive outcomes with data. Ph.D. in CS: Overcame challenges to earn a Ph.D. in a field with low female representation. Passionate about diversity and inclusion in tech. Deep Learning for Computer Vision: Explained the process and its applications in healthcare, transportation, security, etc. Mentoring & Teaching: Advocated for diversity through communities and mentored future generations in tech. Highlighted the importance of introducing data science concepts to K-12 students. Deep Learning for Levee Systems: Used data science to understand levee systems and improve flood risk mitigation.

Career Path: Business Intelligence Developer -> Data Engineer at a pizza chain  Passion: Using data to improve public health and social well-being Skills: Data analysis, ETL design, data warehousing best practices Research: Published paper on maternal stress and child sleep, ensured data accuracy for social science research Data Ethics: Committed to maintaining data integrity and privacy, especially for health data Project Management: Experience supporting researchers with health and minority data Diversity & Inclusion: Works to address undercoverage bias and promote data fairness Journey to STEM: Debunks myths about data science  Mentorship: Facilitates Python programming and mentors junior data scientists

Blogging: Process behind the 60+ posts Fighting Fraud with AI: A deep dive into using neural networks to verify your signature. Balancing school, work, and projects for academic success Uncovering the root cause of business problems. How early roles fueled data career. Climbing the Ladder at CIBC: A journey from intern to Data Quality Analyst.

Career Shift: Transitioning from Data Scientist to Solutions Architect at Databricks. Solutions Architect Role: Designing and implementing data-driven solutions for complex healthcare challenges. Data Science Expertise: Leveraging prior experience to build a strong foundation in the new role. Specialization: Focusing on the Healthcare and Life Sciences sector, building on experience at Hitachi Solutions