Women In Data Science

HighlightsGoogle’s new Agent Development Kit (ADK) (3:16)Getting production agents ready (8:33)Taking risks in career (11:10)Balancing life (13:22)How being a WiDS Ambassador impacted Shir’s career (19:31)BioShir Meir Lador leads a team evangelizing applied AI at Google cloud. Previously, she worked as the AI group Manager of the Document Intelligence Group at Intuit, where she led teams in developing AI services that helped consumers and small businesses prosper. Prior to intuit, sheworked at 2 Israeli startups as a data scientist and researcher.A recognized leader in AI and data science, Shir is a former WiDS Tel Aviv Ambassador, co-founder and organizer of PyData Tel Aviv, and co-host of Unsupervised, a podcast exploring the latest in data science. She frequently speaks at international AI and data science conferences, sharing insights on applied machine learning and AI innovation.Shir holds an M.Sc. in Electrical Engineering and Computers from Ben-Gurion University, specializing in machine learning and si

HighlightsTime at Mathworks (17:27)Being a team leader (18:52)Staying in touch with the technical side (20:04)Advice (27:07)BioSohini Sarkar is a Principal Product Manager and a Senior Team Lead at MathWorks. Her career started with earning a Ph.D. in Civil Engineering and then working on DOE and EPA projects as a postdoctoral researcher. She has held various positions at Dassault Systèmes, ranging from a solution consultant to a market and competitive intelligence analyst, concurrently earning her MBA. Currently at MathWorks, Sohini focuses on established areas such as Math, Statistics, Optimization, and Machine Learning, to more emerging technologies such as Quantum Computing, Large Language Modeling and Generative AI, as well as Scientific Machine Learning.Connect with SohiniSohini Sarkar on LinkedinConnect with UsChisoo Lyons on LinkedInFollow WiDS on LinkedIn (@Women in Data Science (WiDS) Worldwide), Twitter (@WiDS_Worldwide), Facebook (WiDSWorldwide), and Instagram (wids_worldwide)Listen and Subscribe

Predictive Modeling (4:15) Human judgement and processes (14:06)Imperfection in models (21:40)BioClaudia Perlich is Managing Director and Head of Strategic Data Science for Investment Management at Two Sigma, where she has worked for seven years. In this role, Claudia is responsible for developing innovative alpha strategies at the intersection of alternative data, thematic hypotheses and machine learning in public markets. Claudia joined Two Sigma from Dstillery, an AI ad targeting company, where she worked as Chief Scientist. Claudia began her career in data science at the IBM Watson Research Center, concentrating on research in data analytics and machine learning for complex real-world domains and applications.Since 2011, Claudia has served as an adjunct professor teaching Data Mining in the M.B.A. program at New York University’s Stern School of Business. Claudia received a Ph.D. in Information Systems from Stern School of Business, New York University, holds an M.S. of Computer Science from Colorado Univ

HighlightsVulnerability and honesty in leadership (12:07)Finding leaders who are willing to take risks on talent (13:48)BioMaritza is an engineering manager at Klaviyo, where she leads a team focused on creating tools that help marketers better understand and optimize their campaign and flow performance. She enjoys collaborating with her team to develop solutions that provide clear, actionable insights for users.Before joining Klaviyo, Maritza worked at startups in the clinical trial management and natural language processing (NLP) sectors, where she gained experience in applying software to solve practical challenges. She began her career as a research assistant in a computational neuroimaging lab, where she was introduced to software development through the lab's open-source projects. This experience sparked her interest in using technology to address real-world problems.Outside of work, Maritza enjoys knitting, though much of her time is happily spent caring for her 1- and 3-year-olds. Connecting with Mari

Math and Computer Science (2:51)Graph Alignment (20:38) BioHuda Nassar is a senior computer scientist at RelationalAI working on building the graph algorithms library offered as part of RelationalAI's product. Previously, Huda obtained a PhD in Computer Science from Purdue University and was a postdoc fellow at Stanford's School of Medicine. Huda is also known for her "Julia for Data Science" course which had over 13,000 students and focused on Data Science methods including graph analytics. Connect with HudaHuda Nassar on LinkedinConnect with UsMargot Gerritsen on LinkedIn Follow WiDS on LinkedIn (@Women in Data Science (WiDS) Worldwide), Twitter (@WiDS_Worldwide), Facebook (WiDSWorldwide), and Instagram (wids_worldwide)Listen and Subscribe to the WiDS Podcast on Apple Podcasts, Google Podcasts, Spotify, Stitcher

Language as the access to different cultures (2:09)Career journey (8:23)People first in leadership style (23:19)BioHannah Pham is a seasoned data leader with experience building and scaling data teams at top tech companies like Airbnb and Pinterest. Hannah's expertise spans consumer and monetization domains. As the Head of Data Science for the consumer area at Pinterest, she leverages data to bring the best experience to Pinners and drive business growth. Hannah is also a successful startup founder with Skin AI, a personalized skincare company that she co-founded in 2018. Connect with HannahHannah Pham on LinkedinConnect with UsChisoo Lyons on LinkedInFollow WiDS on LinkedIn (@Women in Data Science (WiDS) Worldwide), Twitter (@WiDS_Worldwide), Facebook (WiDSWorldwide), and Instagram (wids_worldwide)Listen and Subscribe to the WiDS Podcast on Apple Podcasts, Google Podcasts, Spotify, Stitcher

Sydney Hazen, a Privacy Data Scientist at Ford, shares her journey from a college intern to a full-time role. She highlights how internships can lead to job offers and the importance of real-world experience and corporate navigation. Sydney emphasizes applying technical skills with a socially conscious approach, understanding problems before diving into data, and credits her professor and diverse classmates for shaping her perspective. She plans to pursue further education and explore different roles, underscoring the unique position of women in data science and the need for self-advocacy and finding mentors.HighlightsInternship at Ford (8:25)Time at Notre Dame (14:55Influencers (17:54)BioSydney is a Privacy Data Scientist at Ford Motor Company, as a part of the Ford College Graduate (FCG) rotational program. She is a recent graduate of the University of Notre Dame, with a degree in Applied and Computational Mathematics and Statistics (ACMS) and a minor in Data Science. She has a range of experience spanning

SummaryListen to Karin Golde, a linguistic expert and AI entrepreneur, as she discusses the rise of large language models (LLMs) and the impact of ChatGPT. Karin reflects on the unexpected popularity of LLMs and the role of OpenAI. The challenges and limitations of LLMs are discussed, including the need for human understanding emphasizing the need for diverse perspectives and cultural understanding in AI development. Karin shares her personal experience of using LLMs and highlights the importance of balancing innovation with regulation in the AI industry. Karin concludes the podcast sharing about her career journey and her recent transition to working as an independent consultant. She offers advice for women considering leadership roles and emphasizes the importance of thinking broadly about one's place in an organization.HighlightsLLMs (1:46)AI systems (3:25)The need for humanness in AI (20:17)Transitioning to independent consultant (28:31)BioKarin Golde, is the Founder of West Valley AI. She helps businesse

 Highlights: 00:02:25 - Colleen’s motivation for writing a book, interdisciplinary collaborations, and explaining advanced mathematical tools in accessible ways.00:08:44 - Journey from biology and social sciences to data science, and the integration of different mathematical tools in solving data problems.00:14:13 - Overcoming imposter syndrome and the value of exploring beyond one's field.00:15:02 - The importance of mentorship.00:23:40 - Coping strategies for setbacks in academia and industry.About the Guest:Colleen Farrelly is an author and senior data scientist. Her research has focused on network science, topological data analysis, and geometry-based machine learning. She has a master's from the University of Miami and has experience in many fields, including healthcare, biotechnology, nuclear engineering, marketing, and education. Colleen wrote the book, The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R.  Mentions:Connect with Colleen Farrelly on LinkedIn Related Links:The Shape

Summary:Listen to the incredible and inspiring journey of Avalon Baldwin’s career journey. A self-described data nerd, she was not only the first in her family to attend college, she went on to get a graduate degree. Today she is an entrepreneur running her own consulting company. In conversation with Chisoo Lyons, Avalon shares how curiosity, mentorship, and coaching made a difference in her life. Highlights: (06:18): Exploring factors like how data is collected, the intention behind collecting a specific data point instead of another one, and how they can influence analysis and interpretation.(08:20): Working with students as individuals and promoting self-agency, as able to influence their own future. (12:02): Avalon describes her journey to become the first in her family to be a college student(32:02): Advice on finding a mentor. About the Guest:Avalon Baldwin master's degree in positive developmental psychology and evaluation from the Claremont Graduate University. She received her bachelor's degree in b

In this episode, Margot Gerittsen speaks with Kim Grauer. Kim is the Director of Research at Chainalysis, where she examines trends in cryptocurrency economics and crime. Listen as she talks about her obsession with fighting fraud in the cryptocurrency market.Highlights:What is crypto crimeTrust in stable coinMisconceptions around cryptocurrencyUsing data and data science in fighting fraud About the Guest:Kim is the Director of Research at Chainalysis, where she examines trends in cryptocurrency economics and crime. She was trained in economics at the London School of Economics and in politics at Oxford University. Previously, she explored technological advancements in developing countries as an academic research associate at the London School of Economics and was an economics researcher at the New York City Economic Development Corporation. Related Links:ChainalysisNew York City Economic Development Corporation Connect with UsMargot Gerritsen on LinkedInFollow WiDS on Twitter (@WiDS_Worldwide), Facebook (WiD

Michelle Katics, CEO  and co-founder of  BankersLab, discusses her journey in risk management training and the importance of integrating technical skills with business and soft skills. She shares her experience in helping banks navigate complex regulations and the need for training to improve understanding and decision-making. Katics emphasizes the importance of storytelling and simplifying complex concepts to effectively communicate with stakeholders. She also highlights the need for women to participate in data science and entrepreneurship, and encourages everyone to continue learning and collaborating to drive innovation and growth. Katics also discusses her involvement in volunteer work, including supporting migrants and refugees and mentoring aspiring entrepreneurs. She concludes by encouraging listeners to embrace diverse skill sets and collaborate to achieve better outcomes.Highlights:Why Michelle went into risk management and why it’s so critical for enterprise success (00:58)Blending business and sof

In this episode, Mary Krone explores her career shift from a PhD in chemistry and biochemistry to data science, where she builds financial credit models. She highlights her work’s tangible impact and discusses the challenges of work-life balance.Mary’s passion for data science’s positive potential in finance shines through as she debunks misconceptions, talks about career paths, and dives into the evolving world of data science and generative AI.The episode also includes topics of the need for continuous learning and the blend of art and science in data science. Highlights: Mary’s transition from doing theoretical work to work in the real world (00:34)It takes a “village” to be successful (10:06)Managing a team of data scientists and why she describes herself as “leading teams who use data science for good” (21:01)Mary’s views and optimism about the data science field (33:25)Women’s roles in the future of data science (45:07)Mentions:Connect with Mary Krone on LinkedInBios:Mary Krone believes in using data sc

Kate Kolich serves as the Assistant Governor and the General Manager of Information Data and Analytics at the Reserve Bank of New Zealand. With an extensive background in the financial sector, she also has significant public sector experience. Throughout her impressive career, she's delved into areas like data analytics, digital strategy, information management, data governance, business intelligence, and data warehousing, among others. Soon after the launch of Women in Data Science (WiDS) at Stanford, Kate became an active WiDS ambassador. She has organized numerous WiDS conferences in New Zealand, spotlighting nearly 100 female data scientists. Beyond this, Kate is a passionate mentor and supporter of many professionals in New Zealand. In this episode, we discuss Kate's role at the Reserve Bank, the role of her team, highlights from her career, and her insights on being a successful woman leader in her field.For Detailed Show Notes visit our website.In This Episode We Discuss:Kate’s role at the Reserve Bank

Telle Whitney began her career in the tech industry in 1986 after earning a Ph.D. in computer science from Cal Tech. Her journey into graduate studies was sparked by an encounter with graphics during her undergraduate studies at the University of Utah. Although she initially wasn't interested in graphics, the idea of computer-aided design fascinated her, and she was drawn to work with Ivan Sutherland, a co-founder of the computer science department at Cal Tech.Throughout college, Telle learned various programming languages, starting with C as an undergraduate and later delving into object-oriented languages like Simula and Mainsail. While she hasn't programmed in years, Telle acknowledges that programming languages evolve and change rapidly, but once you understand the core concepts, transitioning to a new language becomes relatively easy.Reflecting on her path into computer science, Telle admits that she had no exposure to the field during high school, which is a common experience for many young girls. “It w

Srujana Kaddevarmuth began her career near Bangalore, India after completing her master’s degree in engineering from Visvesvaraya Technological University. She has had a successful career in the tech industry and currently holds the position of senior director at Walmart's Data and Machine Learning Center of Excellence.In her role as senior director at Walmart, Srujana leads the AI portfolio for various aspects of the company's retail business, including omni retail, new and emerging businesses in the consumer and tech space, data monetization, and membership. Her primary responsibility is to drive innovation and promote the democratization of data and AI, aiming to create value for consumers, associates, and the business as a whole.Despite coming from an academic family, Srujana chose to pursue a career in the corporate sector rather than academia. After obtaining her bachelor’s degree in engineering, she gained real-world exposure to data science and AI while working at the Energy and Resources Institute. T

Today Veronica Edwards is a senior data analyst at Polygence, though her educational and career background encompasses a wide range – she has delved into everything from dance and choreography to physics, sociology, marketing, and most recently, data science. Polygence is a nonprofit that offers middle and high school students a 10-week research experience under the guidance of a professional mentor. As a senior data analyst at Polygence, Veronica uses data to help build and scale the company and to provide students and mentors with an optimal experience.Upon working at Polygence, Veronica was surprised to learn how little high school students are asked to do independent research. Independent research affords students the opportunity to explore their passions, get comfortable with the ambiguity of the research process, and become experts on their chosen topic. Polygence aims to democratize this research experience and has successfully targeted a diverse selection of program participants, attracting mentors an

As Estée Lauder’s first-ever Chief Data Officer, Jane Lauder is combining data science with creativity to fuel the growth of the company. Jane has worked at Estée Lauder for 26 years – 24 of which she spent working on the brand and marketing aspects of the business. While working as the Global Brand President of Clinique, Jane saw the power of data to drive all aspects of the business, motivating her to transition into her current role. Estée Lauder Companies is one of the world’s leading manufacturers and marketers of luxury skincare, makeup, fragrance, and hair care products. It encompasses a house of about 30 brands including their flagship brand Estée Lauder, as well as other brands such as Clinique, Crème de la Mer, MAC, Jo Malone, Aveda, Le Labo, Bobbi Brown, Origins, Dr.Jart+, Too Faced cosmetics, and more. The beauty giant was founded by Jane’s grandmother, Estée Lauder, over 75 years ago. Before there were data and analytics to pull from, Estée Lauder would gather information about potential consumer

An expert in climate change and the optimization of power grids, Priya Donti researches how to use machine learning for forecasting, optimization, and control of power grids to facilitate the integration of renewable energy. She first became interested in climate change during high school and studied computer science with a focus on environmental analysis as an undergraduate at Harvey Mudd College. After graduation, she spent a year on a Watson Fellowship, learning about different approaches for next-generation power grids in Germany, India, South Korea, Chile, and Japan. She went on to earn her PhD in power grid optimization at Carnegie Mellon. While there, she co-founded Climate Change AI, an initiative born out of a paper she co-wrote with academic and industry leaders about the ways machine learning could address climate change.Machine learning can play a role in mitigating climate change in areas like decarbonizing power grids, buildings, and transportation; helping create more precise forecasts for clim

Lesly Zerna earned her undergraduate degree in Telecommunications Engineering at the Bolivian Catholic University and then traveled to Brussels to complete a Masters in Computer Science. After returning to Latin America, she began teaching data science and AI both in universities and virtual platforms and today her courses have thousands of online students. She brings insights from her experiences working in large companies overseas to her students in Latin America. For those just starting in data science, she says you must first identify your personal learning style (e.g., visual or text) to improve your learning experience and start with a general overview of the field. Next, find a practical topic you’re interested in, and look for projects, examples, authors, researchers who are working in that area. Do all of this while continuing to develop the fundamental skills you need (e.g., languages, platforms, frameworks) in data science. Lesly transmits her passion for learning to her students by using real scen