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Phase AI is a community for data professionals to connect, learn, and advance their careers
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Data Science Webinars
 
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Planning Your Path: How To Become a Leader in Data and AIMarch 13, 2024 Having a long-term career plan is incredibly important, even before you land that first data/AI job. This webinar covers hiring trends in 2024, career paths to consider, and frameworks for long-term career planning. |
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Getting Ahead and Staying Ahead: Interviewing and Upskilling for Data/AI/ML RolesNovember 10, 2023 It seems employers are constantly looking for something new and different from potential employees. This webinar covers the skills that employers are looking for, and how you can upskill — both early on in your AI career and as an experienced professional. |
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Launching your AI/Data Career in 2023March 30, 2023 This webinar covers recent labour market trends and what they mean to students and researchers launching their data/AI careers. Learn which employers are hiring, the skillsets with increasing demand, and how to stand out. We review tactics and advice around personal branding, how to invest in and use side projects to your advantage, and how to use non-technical skills and experiences to improve your chances of landing your dream job. |
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Career Pathing: From Data Analyst to Data Science ManagerApril 21, 2021 at 12:00pm Eastern Time We spoke with Yichen Huang, Data Science Manager at Drop Technologies. Yichen studied business and economics, started her career as a data analyst, and today manages a data team. Hear how she navigated her career and her leadership approach to data in startups. |
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Acing Data & AI InterviewsMarch 18, 2021 at 12:00pm Eastern Time In this session, we explore what to expect from and how to prepare for a job interview. Learn to master both the technical and non-technical components in interviewing. |
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Nuances of Data Roles and “Hybrid” Career TrajectoriesMarch 3, 2021 at 12:00pm Eastern Time The AI landscape is evolving and so too are the diverse array of data/AI career pathways possible. This webinar explores types of data roles, required skill sets, and strategies for applying for these roles. |
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Accelerating Your Career via Your Online PresenceFebruary 12, 2021 at 12:00pm Eastern Time Your online presence won’t just get you your next job, it’ll accelerate your entire career trajectory. This session will show you how employers seek talented AI hires, and how you can optimize your profile to ensure you stand out in their recruiting processes. |
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Best Practices for Building Computer Vision ModelsJanuary 20, 2021 at 11:00am Eastern Time You can't build self-driving cars or computer generated films without computer vision. And for that you need copious amounts of image data. Luis Bermudez is a Research Scientist at Intel's Applied Machine Learning team, where he solves customer problems with ML solutions to significantly accelerate existing workflows. |
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Effective Data Science in the EnterpriseDecember 4, 2020 at 1:00pm Eastern Time From navigating organizational structures to leveraging data lifecycles and workflows, Lisa will provide advice on how to grow a career in enterprise data and analytics based on her 16 year career in the industry. |
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Decision Science: Translating Data Insights to Corporate Decision MakingNovember 24, 2020 at 1:00pm Eastern Time What are the common pitfalls data scientists face when trying to influence decisions, both operational and strategic? 'Decision science' guides corporate decision making, and can be used to make smarter decisions such as which sales lead to follow or which marketing tactic to deploy. |
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Navigating a Data Career: Academia, Data Science, Product ManagementNovember 17, 2020 at 12:00pm Eastern Time Join Jesse Day as he discusses his evolution from academic research, to data science, to product management. This talk covers transitioning from a PhD to data science, working at a startup, and much more. |
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Moving from Software Engineering to Machine LearningNovember 11, 2020 at 12:00pm Eastern Time Matthew Beleck discusses the differences between software engineering and ML projects. Data projects often present unique challenges to engineers, as data quality and availability can impact your ability to complete a product build. |
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Best Practices for NLP Data Collection and DesignNovember 10, 2020 at 6:00pm Eastern Time You can't build NLP-powered products and services without robust, detailed data sets. Unfortunately, building such data sets can be time consuming and expensive; a poorly designed data set will also prevent your models from actually helping users. Ivan Lee discusses best practices for data set design and labelling. |
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Tips and Perspective on Starting Your Data Science CareerNovember 5, 2020 at 12:00pm Eastern Time Data Science is a broad field with numerous core competencies and specializations. In this talk, Justin explores some of necessary skills for transitioning from learning data science to doing data science in an R&D setting, in both government and private industry. |
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Building Products Powered by Data and MLOctober 28, 2020 at 6:00pm Eastern Time Launching data products using a traditional product approach is challenging. Amber Foucault will share the importance of creating "data networks" that can power multiple applications and features, and discuss how you must think differently about validation when building data products. |
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Help Your Manager Help You Build the Career You WantOctober 26, 2020 at 1:00pm Eastern Time Jessica Hastings, VP of Analytics at Betterment, will talk about how you can maximize this relationship and empower your manager to be your best advocate. She’ll share insight into the manager mindset, strategies for tailoring formal and informal communication with your manager, and suggestions for how to refine your own vision for what you want to achieve. |
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Starting and Managing a Career in Natural Language ProcessingOctober 22, 2020 at 6:00pm Eastern Time Natural Language Processing (NLP) helps companies understand documents, emails, and other unstructured text data. It's a fast-growing field with companies hiring analysts, product managers, and researchers to help launch NLP-driven products. This webinar will discuss trends in NLP and ways you can start a career focusing on this popular area of machine learning. |
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Building and Leveraging Your Online ProfileOctober 21, 2020 at 6:00pm Eastern Time Join Andrew Savage, Data Recruiter at Faire, in this talk about how to stand out in the online crowd of data professionals. This session is for job seekers who are ready to apply for jobs but are looking for ways to better stand out in the crowd on LinkedIn and other online tools. |
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Marketing Analytics in the CPG IndustryOctober 14, 2020 at 1:00pm Eastern Time Justin Mathew is a marketing data scientist in the oral care business at Proctor & Gamble. He will join us for a conversation about how he started his career and how he brings data science to the forefront of marketing and media within the CPG industry. |
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From Physics PhD to Applied MLOctober 13, 2020 at 2:00pm Eastern Time Jorge Escobedo completed a PhD in String Theory, and then cofounded a YC-backed AI-focused customer data company. After a successful exit, Jorge Escobedo joined Drop as the Head of Data and Machine Learning. He now leads their technology function as VP of Engineering. |
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Hybrid Data ScientistsOctober 9, 2020 at 2:00pm Eastern Time "Hybrid data scientists" are people who have a strong set of experiences in non-analytics and combine this experience with data/analytics to build unique career paths. Andrea Yip will discuss her interviews with logistics experts turned data scientists, biotech researchers who have moved into marketing analytics, and more. |
Career Advice
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Best Free Resources for Learning AI/ML in 2024November 20, 2023 A list of our favorite free resources for learning AI and ML. These are vetted by the Phase AI team and include textbooks, lecture videos, and entire courses. |
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Top Natural Language Processing Labs in AcademiaMay 5, 2021 We’ve compiled a list of the leading Natural Language Processing (NLP) Labs across the United States, Canada, and the United Kingdom that are based out of academic institutions. We hope this is a helpful resource and inspiration for your own NLP work. |
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An Introduction to Feature StoresApril 8, 2021 Feature Stores are an architecture component and product option that can dramatically change data science workflows and make you significantly more productive. |
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Types of ML-Driven Products, and How to Build ThemMarch 25, 2021 When designing ML-driven products, it's important to distinguish those which are focused on analytics, automation, and magic. We provide an overview of all three along with guidelines for ML-driven product design. |
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Data Portfolios from Recent AI GraduatesMarch 18, 2021 This post includes a collection of portfolios from students and recent graduates affiliated with the Vector Institute, a leading AI research institute. |
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A Checklist for Preparing your Data/AI PortfolioFebruary 23, 2021 There is no right or wrong way to put together a portfolio. However, among the portfolios we consider to be strong, memorable, and more likely to get noticed by an employer, we’ve noticed a few consistent themes. Here is our checklist for best practices when it comes to creating a data/AI portfolio. |
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Preparing for data science interviews with a coachFebruary 4, 2021 Working with a coach to prepare for an upcoming interview is a great strategy. We provide an overview of approaches to working with a coach, and how to make it most effective for candidates. |
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Phase AI collaborates with Vector Institute to help AI graduates accelerate their careersFebruary 2, 2021 Phase AI and the Vector Institute will provide programming to 2,000 AI graduates from Ontario through a series of webinars and personalized coaching sessions. |
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Data Portfolios from the Phase AI CommunityJanuary 20, 2021 Data portfolios showcase the unique talents of a data professional. Portfolios come in many different shapes and forms. This post shows examples of data portfolios from the Phase AI community. |
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Book Review: Machine Learning Design PatternsJanuary 6, 2021 An oft-overlooked area of data science is the actual architecture of machine learning systems. This book provides an overview of common design patterns for planning, building, and scaling ML systems. |
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Skills and Qualities of Top Tier ML ResearchersDecember 8, 2020 ML Researchers don't just need to build models, they need to understand how to define problems, build data sets, and implement research papers. Learn what defines top tier researchers. |
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Six tips for applying for jobs on our data science jobs boardDecember 1, 2020 The Phase AI data science jobs board has dozens of new jobs posted daily. Learn how you can stand out in the crowd of applicants with these six tips. |
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The Best Data Portfolios on the WebNovember 23, 2020 Many of you asked for examples of stellar portfolios, so we searched the web and found diverse portfolios that demonstrate how folks have taken different approaches to showcasing their work. |
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A data recruiter's guide to standing out of the online crowdNovember 10, 2020 Data science is a crowded industry. Standing out and getting noticed by potential employers and collaborators can be challenging. Here are 7 tips on how to get your accomplishments as a data professional noticed online. |
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Preparing for your first screening call for a data roleNovember 4, 2020 A first step in any hiring process is the initial screening call. Here are our top recommendations for preparing for your next screening call... |
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The Power of Hybrid Data ScientistsOctober 29, 2020 “Hybrid” data scientists are individuals who have made a pivot into data science (as scientists, analysts, engineers, etc.) from a non-data profession. It’s a powerful way to distinguish yourself from other applicants. |
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Put together a data science portfolio and get noticedOctober 20, 2020 An important part of seeking a data-oriented job is putting together a data science portfolio. Portfolios help candidates stand out to hiring managers and potential companies they could work at. |