Dataframed

Today marks the last episode of our four-part DataFramed Careers Series on breaking into a data career. We’ve heard from Sadie St Lawrence, Nick Singh, and Khuyen Tran on best practices to adopt to help you land a data science interview. But what about the interview itself? Today’s guest, Jay Feng, joins the show to break down all the most important things you need to know about interviewing for data science roles. Jay is the co-founder of Interview Query, which helps data scientists, machine learning engineers, and other data professionals prepare for their dream jobs. Throughout the episode, we discuss The anatomy of data science interviews Biggest misconceptions and mistakes candidates make during interviews The importance of showcasing communication ability, business acumen, and technical intuition in the interview How to negotiate for the best salary possible [Announcement] Join us for DataCamp Radar, our digital summit on June 23rd. During this summit, a variety of experts from different backgrounds

Today is the third episode of this four-part DataFramed Careers series being published every day this week on building a career in data. We’ve heard from Nick Singh on the importance of portfolio projects, as well as the distinction between content-based and coding-based portfolio projects. When looking to get started with content-based projects, how do you move forward with getting yourself out there and sharing the work despite being a relative beginner in the field?Today’s guest tackles exactly this subject. Khuyen Tran is a developer advocate at prefect and a prolific data science writer. She is the author of the book “Efficient Python Tricks and Tools for Data Scientists” and has written 100s of blog-articles and tutorials on key data science topics, amassing thousands of followers across platforms. Her writing has been key to accelerating here data career opportunities. Throughout the episode, we discuss: How content creation accelerates the careers of aspiring practitioners The content creation process

Today marks the second episode in our DataFramed Careers Series. In this series, we will interview a diverse range of thought leaders and experts on the different aspects of landing a data role in 2022. In the first episode of the series, Sadie discussed at great length the importance of having a solid data science portfolio to land a role in data. But what makes a great data science portfolio? Nick Singh, co-author of Acing the Data Science Interview, joins the show to share everything you need to know to create high-quality, thorough portfolio projects. Throughout the episode, we discuss How portfolio projects build experience Who should be focusing on portfolio projects The different types of portfolio projects Biggest pitfalls when creating portfolio projects How to get noticed with your portfolio projects Concrete examples of great portfolio projects  [Announcement] Join us for DataCamp Radar, our digital summit on June 23rd. During this summit, a variety of experts from different backgrounds will be

Today is the start of a four-day careers series covering breaking into data science in 2022. With so so much demand for data jobs today, we wanted to demystify the ins and outs of accelerating a career in data. In this series, we will interview a diverse range of thought leaders and experts on the different aspects of standing out from the crowd in the job hunt. Our first guest in the DataFramed Careers Series is Sadie St. Lawrence. Sadie St Lawrence is the Founder and CEO of Women in Data, the #1 Community for Women in AI and Tech. Women in Data is a community of over 20,000 individuals and has representation in 17 countries and 50 cities. She has trained over 350,000 people in data science and is the course developer for the Machine Learning Certification for UC Davis. In addition, she serves on multiple start-up boards, and is the host of the Data Bytes podcast. Sadie joins the show to talk about her career journey in data science and shares the best lessons she has learned in launching data careers. Throu

Introducing the DataFramed Careers Series. Over the past year hosting the DataFramed podcast, we've had the incredible privilege of having biweekly conversations with data leaders at the forefront of the data revolution. This has led to fascinating conversations on the future of the modern data stack, the future of data skills, and how to build organizational data literacy.  However, as the DataFramed podcast grows, we want to be able to provide the data science community across the spectrum from practitioners to leaders, with distilled insights that will help them manoeuvre their careers effectively. And we want to do that more often.  This is why we’re excited to announce the launch of a four-day DataFramed Careers Series. Throughout next week, we will interview four different thought leaders and experts about what it takes to break into data science in 2022, best practices to stand out from the crowd, building a brand in data science, and more. Moreover, this episode series will mark DataFramed’s transitio

Data literacy at any organization takes buy-in from all levels of the company, from C-suite leaders all the way to customer-facing team members. But how do you get that buy-in, build a team around data literacy, and transform the way your company works with data? Today’s guest, Megan Brown, Director of Data Literacy and Knowledge Management at Starbucks, discusses what they have done to forge data culture and data literacy at Starbucks. Throughout the episode, we discuss How to increase data literacy in an organization How to secure executive sponsorship for data initiatives The importance of user experience research in building data literacy  Balancing short-term business needs with long-term strategic upskilling Humanizing machine learning and AI within the organization 

Diversity in both skillset and experience are at the core of high-impact data teams, but how can you take your data team’s impact to the next level with subject matter expertise, attention to user experience, and mentorship? Today’s guest, Dan Kellet, Chief Data Officer at Capital One UK, joins us to discuss how he scaled Capital One’s data team. Throughout the episode, we discuss: The hallmarks of a high-impact data team The importance of skills and background diversity when building great data teams The importance of UX skills when developing data products The specific challenges of leading data teams in financial services

As data volumes grow and become ever-more complex, the role of the data analyst has never been more important. At the disposal of the modern data analyst, are tools that reduce time to insight, and increase collaboration. However, as the tools of a data analyst evolve, so do the skills.  Today’s guest, Peter Fishman, Co-Founder at Mozart Data, speaks to this exact notion.  Join us as we discuss: Defining a data-driven organization & main challenges Breaking down the modern data stack & what it means What makes a great data analyst How data analysts can develop deep subject matter expertise in the areas they serve Find every episode of DataFramed on Apple, Spotify, and more. Find us on our website and join the conversation on LinkedIn. Listening on a desktop and can’t see the links? Just search for DataFramed in your favorite podcast player.

When you hear the term-digital first, you might think about tech, platforms and data.  But digital transformation succeeds when you put people first. Gathering and analyzing data, then using it to provide the customer value and an unparalleled experience, is vital for an organization’s success. Today’s guest, Bhavin Patel, Director o f Analytics and Innovation at J&J joins the show to share why people are the most important component to digital transformation. Join us as we discuss: Why you need to put people first The importance of customer value and experience Why digital transformation is an ongoing process, not an end-state  Find every episode of DataFramed on Apple, Spotify, and more. Find us on our website and join the conversation on LinkedIn. Listening on a desktop and can’t see the links? Just search for DataFramed in your favorite podcast player.

The data journey is a slow painstaking process. But knowing where to start and the areas to focus on can help any organization reach its goals faster. Today’s guest, Vijay Yadav, Director of Quantitative Sciences & Head of Data Science at the Center for Mathematical Sciences at Merck, explains the 6 key elements of data strategy, complete with advice on how to navigate each. Join us as we discuss: The different components of a data strategy Shifting mindset within the C-Suite Structuring the operating model Enabling people to work with data at scale Most effective tactics to kickstart a community around data science Find every episode of DataFramed on Apple, Spotify, and more. Find us on our website and join the conversation on LinkedIn. Listening on a desktop and can’t see the links? Just search for DataFramed in your favorite podcast player.

It’s no secret that data science jobs are on the rise; but data skills across the board are rising — leading to what today’s guest calls “hybrid jobs.” This will require a paradigm shift in how we think about jobs and skills.   Today’s guest, Matt Sigelman, President of The Burning Glass Institute & Chairman of Emsi Burning Glass, talks about the difficulties of connecting companies with top talent, the hybridization of many positions, and how to position yourself in the ever-changing market.  Join us as we discuss: The methodology of using data science on the labor market The demand for data skills & how they’re evolving Blending skills to get ahead in the job market & the rise of subskills How educational institutions can prepare students for hybridization  Advice to the audience on how to structure their approach to skill acquisition  Find every episode of DataFramed on Apple, Spotify, and more. Find us on our website and join the conversation on LinkedIn. Listening on a desktop and can’t s

Throughout the middle east, efforts are underway to build smart cities from the ground up. But to create a modern, intelligently-designed city, you first need to lay a solid foundation. And the strongest foundation you can build a smart city upon is data. In today’s episode, we speak with Kaveh Vessali, Digital, Data & AI Leader, PwC Middle East, about the intersection between data and public policy and the many exciting insights he’s gained from his role delivering smart cities and data transformation projects within the public sector in the middle east.  Join us as we discuss: The important role data plays in shaping public policy  What goes into designing a smart city The change management skills vital for successful digital transformation  Data ethics and the importance of transparency   Find every episode of DataFramed on Apple, Spotify, and more. Find us on our website and join the conversation on LinkedIn.  Listening on a desktop and can’t see the links? Just search for DataFramed in your favorit

When most people hear digital transformation, it’s almost always the technology that first springs to mind. That’s a mistake. You can have the most sophisticated tech stack in the world, but if you don't build your organization’s data culture, your digital transformation efforts will be for naught. Today’s guest, Mai AlOwaish, Chief Data Officer at Gulf Bank, knows this better than anyone. As the first female CDO in Kuwait, she’s on a mission to ensure everyone at Gulf Bank becomes an expert in the data they use every day. Join us as we discuss: Why data and people are more important than technology for digital transformationThe pioneering Data Ambassador program Mai spearheaded at Gulf BankThe importance of diversity in data science and technology overall Find every episode of DataFramed on Apple, Spotify, and more. Find us on our website and join the conversation on LinkedIn. Listening on a desktop and can’t see the links? Just search for DataFramed in your favorite podcast player. 

As we enter the new year—it seems like we’re telescoping into the future of work. Companies embracing remote work, the great resignation putting pressure on teams to create more fulfilling roles—signals an expanding opportunity for applicants to find their dream roles in data science, but also for hiring managers to create awesome candidate experiences.  Today’s guests, Nick Singh, and Kevin Huo, authors of Ace The Data Science Interview, discuss how aspiring data scientists and data scientists can stand out from their crowd—and what hiring managers need to change to win over talent today.  Join us as we discuss: How to wow recruiters and hiring managers with your resumeThe type of skills aspiring data scientists need to show on the job huntThe value of direct email over job listingsWhat recruiters and hiring managers need to change in an evolving job market Relevant links from the interview: Ace the Data Science InterviewFollow Nick Singh on LinkedInFollow Kevin Huo on LinkedInNoah Gift’s Appearance on

In this episode of DataFramed, we speak with Vishnu V Ram, VP of Data Science and Engineering at Credit Karma about how data science is being leveraged to increase financial inclusion. Throughout the episode, Vishnu discusses his background, Credit Karma’s mission, how data science is being used at Credit Karma to lower the barrier to entry for financial products, how he managed a data team through rapid growth, transitioning to Google Cloud, exciting trends in data science, and more.  Relevant links from the interview: You can now learn data science with your team for free—try out DataCamp Professional with our 14-day free trial. Data roles at Credit KarmaCredit Karma’s mission

In this episode of DataFramed, we speak with Andy Cotgreave, Technical Evangelist at Tableau about the role of data storytelling when driving change with analytics, and the importance of the analyst role within a data-driven organization. Throughout the episode, Andy discusses his background, the skills every analyst should know to equip organizations with better data-driven decision making, his best practices for data storytelling, how he thinks about data literacy and ways to spread it within the organization, the importance of community when creating a data-driven organization, and more. Relevant links from the interview: We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second surveyCheck out our upcoming webinar with AndyCheck out Andy's bookBecome a Tableau expert

In this episode of DataFramed, we speak with Brian Campbell, Engineering Manager at Lucid Software about managing data science projects effectively and harnessing the power of collaboration. Throughout the episode, Brian discusses his background, how data leaders can become better collaborators, data science project management best practices, the type of collaborators data teams should seek out, the latest innovations in the data engineering tooling space, and more. Relevant links from the interview: We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second surveyLucid’s Tech Blog

In this episode of DataFramed, we speak with Shameek Kundu, former group CDO at Standard Chartered Bank, and Chief Strategy Officer & Head of Financial Services at TruEra Inc about Scaling AI Adoption throughout financial services. Throughout the episode, Shameek discusses his background, the state of data transformation in financial services, the depth vs breadth of machine learning operationalization in financial services today, the challenges standing in the way of scalable AI adoption in the industry, the importance of data literacy, the trust and responsibility challenge of AI, the future of data science in financial services, and more. Relevant links from the interview: We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second surveyCheck out TruEra in actionBank of England Report: The impact of Covid on machine learning and data science in UK BankingMIT Tech Review — Hundreds of AI tools have been built to catch covid. N

In this episode of DataFramed, we speak with Syafri Bahar, VP of Data Science at Gojek about building high-performing data teams, and how data science is central to Gojek’s success.  Throughout the episode, Syafri discusses his background, the hallmarks of a high-performance data team, how he measures the ROI on data activities, the skills needed in every successful data team, what is the best organizational model for data mature organizations, how Covid-19 affected Gojek’s data teams, his thoughts on data literacy and governance, future trends in data science and AI, and why data scientists should sharpen their maths and machine learning skills in an age of increasing automation.  Relevant links from the interview: We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second surveyGojek’s Data Blog

In this episode of DataFramed, we speak with Noah Gift, founder of Pragmatic AI Labs and prolific author about operationalizing machine learning in organizations and his new book Practical MLOPs.  Throughout the episode, Noah discusses his background, his philosophy around pragmatic AI, the differences between data science in academia and the real world, how data scientists can become more action-oriented by creating solutions that solve real-world problems, the importance of dev-ops, his most recent book on the practical guide to MLOps, how data science can be compared to Brazilian jiu-jitsu, what data scientists should learn to scale the amount of value they deliver, his thoughts on auto-ml and automation, and more.  Relevant links from the interview: We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second surveyUnsettled: What Climate Science Tells Us, What It Doesn't, and Why It MattersCheck out Noah's booksCheck out Noah's c