Women In Tech

Datacast Episode 115: Product-Led Sales, Community-Led Category Creation, and Unlocking Revenue Data with Alexa Grabell

Datacast Episode 115: Product-Led Sales, Community-Led Category Creation, and Unlocking Revenue Data with Alexa Grabell

Alexa Grabell is the co-founder and CEO of Pocus, a Revenue Data platform that is purpose-built for GTM teams to analyze, visualize, and action data about their prospects and customers without needing engineers. 

Alexa’s passion for Product-Led Sales started when she led sales strategy & operations at Dataminr, where she built internal solutions to equip sales teams with data. She studied engineering at Vanderbilt University and received her MBA from Stanford University.

Datacast Episode 96: Data Science Training and The Power of Education with Merav Yuravlivker

Datacast Episode 96: Data Science Training and The Power of Education with Merav Yuravlivker

Merav Yuravlivker is the Co-founder and Chief Executive Officer of Data Society. With over ten years of experience in instructional design, training, and teaching, she started her career teaching elementary special education in NYC public schools through the Teach for America program. She went on to join the International Baccalaureate Organization, where she developed deep expertise in online training, assessments, and recruitment. She also taught as a Kaplan GRE instructor, where she ranked as one of their top 10% instructors based on student surveys.

Merav found her passion for education and knew that she wanted to make an impact on an even larger scale. She recognized the importance of data literacy and began her data journey by learning how to program and design best practices for students during her free time. Six months later, she left her full-time job to focus on building Data Society along with her co-founders. Over the past seven years, she and her team have developed customized, industry-tailored data science training solutions that educate, equip and empower an organization’s workforce to achieve its goals and expand its impact.

Datacast Episode 81: Research, Engineering, and Product in Machine Learning with Aarti Bagul

Datacast Episode 81: Research, Engineering, and Product in Machine Learning with Aarti Bagul

Aarti Bagul is a machine learning engineer at Snorkel AI. Before Snorkel, she worked closely with Andrew Ng in various capacities: (1) at AI Fund helping build ML companies from scratch internally and investing in ML companies, (2) as an ML engineer at his startup Landing AI, (3) as head TA for his deep learning class CS230, and (4) as an assistant in his research lab at Stanford.

Aarti graduated with a master’s in Computer Science from Stanford, where she participated in the Threshold Venture and Greylock X fellowships. Before Stanford, she got her bachelor’s in Computer Science and Computer Engineering from NYU with the highest honors. During her time at NYU, she worked in David Sontag’s lab on machine learning applications to clinical medicine and at Microsoft Research as a research intern for John Langford (where she contributed to Vowpal Wabbit, an open-source project).

Datacast Episode 71: Trusted AI with Saishruthi Swaminathan

Datacast Episode 71: Trusted AI with Saishruthi Swaminathan

Saishruthi Swaminathan is an Advisory Data Scientist at IBM's AI Strategy and Innovation division. Previously, she was a technical lead and data scientist in the IBM Center for Open-Source Data and AI Technologies team, whose main focus is to democratize data and AI through open source technologies. She has a Master’s in Electrical Engineering that specializes in Data Science and a Bachelor's degree in Electronics and Instrumentation. Her passion is to dive deep into the ocean of data, extract insights, and use AI for social good.

Previously, she worked as a Software Developer on a mission to spread the knowledge and experience she acquired in her learning process. She also leads an initiative to bring education to rural children and organizes meetups that focus on women's empowerment.

Datacast Episode 69: DataPrepOps, Active Learning, and Team Management with Jennifer Prendki

Datacast Episode 69: DataPrepOps, Active Learning, and Team Management with Jennifer Prendki

Dr. Jennifer Prendki is the founder and CEO of Alectio, the first startup fully focused on DataPrepOps. She and her team are on a fundamental mission to help ML teams build models with less data. Before Alectio, Jennifer was the Vice President of ML at Figure Eight. She also built an entire ML function from scratch at Atlassian and led multiple Data Science projects on the Search team at Walmart Labs. She is recognized as one of the top industry experts on Active Learning and ML lifecycle management. She is an accomplished speaker who enjoys addressing both technical and non-technical audiences.

Datacast Episode 44: Computer Systems, ML Security Research, and Women in Tech with Shreya Shankar

Datacast Episode 44: Computer Systems, ML Security Research, and Women in Tech with Shreya Shankar

Shreya Shankar is a computer scientist living in the Bay Area. She is interested in making machine learning work in the real world. She currently works at Viaduct — an applied machine learning startup — but most recently, she researched at Google Brain. She graduated from Stanford University with a B.S. in computer science, concentrating on systems. She's finishing her M.S. in computer science, concentrating on artificial intelligence.

Datacast Episode 30: Data Science Evangelism with Parul Pandey

Datacast Episode 30: Data Science Evangelism with Parul Pandey

Parul Pandey is a Data Science Evangelist at H2O.ai. She combines Data Science, evangelism and community in her work. Her emphasis is to break down the data science jargon for the people. Prior to H2O.ai, she worked with Tata Power India, applying Machine Learning and Analytics to solve the pressing problem of load sheddings in India. She is also an active writer and speaker and has contributed to various national and international publications including Towards Data Science, Analytics Vidhya, and KDNuggets and Datacamp.

Datacast Episode 13: Transition From Academia to Data Science with Martina Pugliese

Datacast Episode 13: Transition From Academia to Data Science with Martina Pugliese

Martina is a physicist and works as Data Science Lead at Mallzee, based in Edinburgh (Scotland). She loves looking at data regardless of the topic and area and believes the most enjoyable thing in Data Science is analyzing your data, finding the one you need for your question, and producing facts out of it. Throughout her education and job experience, she worked with data in epidemic dynamics, linguistics, and fashion. She also loves producing hand-crafted data visualizations and keeps studying and improving, whether it’s about Machine Learning or leadership topics.