Today’s guest is Thomas Vincent, Head of Data Science at Getty Images. Thomas is an experienced statistician and programmer who is passionate about developing tools and pipelines to discover and retrieve underlying phenomenons and patterns in modern-day datasets. His work includes predictive analysis, NLP, data visualization and data analysis.
Getty Images is the most trusted and esteemed source of visual content in the world, with over 200 million assets available. They serve creative, business and media customers in almost 200 countries with images from over 200,000 contributors and hundreds of partners to provide comprehensive coverage of more than 130,000 news, sport and entertainment events around the globe.
In the episode, Thomas will discuss:
How they are using AI and Data Science at Getty Images,
Building and scaling a successful data science team,
What their ideal candidate looks like,
Why Getty Images is a great place to work,
How to stand out in the interview process,
What would he do differently if he was to start again,
and What’s in store at Getty Images in the near future.
Today’s guest is Glenn Hofmann, Chief Analytics Officer at New York Life, one of America’s largest mutual life insurance companies. For over 175 years, New York Life and their subsidiaries provide insurance, investment and retirement solutions. They believe in the importance of human guidance and intrusted relationships built on being there when customers need them most.
Glenn is an experienced Senior Executive in Insurance and Financial Services, who currently leads the corporate 50-person Data Science and AI function at New York Life. He is responsible for the foundations, relationships with many internal groups and a great variety of projects. He also leads their Data Science Academy, their internal education program for all New York Life employees.
In the episode, Glenn will discuss:
What he loves about his role at New York Life,
How he helped the company embrace a data-driven culture,
Exciting projects they are working on within the insurance industry,
Creating a successful data science team,
How to stand out in the job application process,
and Key learns in transitioning into a leadership position.
Today’s guest is Paul Brenner, Head of Data Science at PlaceIQ where he defines the role of data science within the company. Paul ensures the team works on the most impactful projects, finds new ways that they can build new products that will fulfil their client’s needs and helps promote education within the organization to keep PlaceIQ ahead of the competition.
Based in New York, PlaceIQ powers critical business and marketing decisions with location data, analytics and insights. Companies can uncover opportunities within the consumer journey by learning about and connecting with location-based audiences, measuring real-world ROI, and applying insights that drive intelligent marketing and successful business outcomes.
In the episode, Paul will discuss:
How he helped grow the Data Science function at PlaceIQ,
The different paths available for Data Scientists,
Advice on deciding when to apply Machine Learning in your business,
What to consider when making your next career move,
Building a high-performing data science team,
and His top interview tips.
Today’s guest is Bob Bress, VP of Analytics and Business Intelligence at Freewheel. Bob is an Analytics leader with 15+ years of experience in developing and implementing complex analytical solutions for leading-edge technology and advertising programs. He is an expert in building Data Science and Business Intelligence teams from the ground up.
Freewheel empowers all segments of The New TV Ecosystem. They power the technology, data enablement, and convergent marketplaces required to ensure buyers and sellers can transact across all screens, across all data types and all sales channels, in order to ensure the ultimate goal in gaining the best results for marketers.
In the episode, Bob will discuss:
Freewheel’s current projects within TV advertising
What he loves about his job
How to add real business value through data science
Key traits to have for a successful data scientist
Building a successful data science team
Advice on how to interview more effectively
Future trends in media & advertising that excite him
Today’s guest is Brigham Hyde PhD, Co-Founder and Advisor at Concerto Health AI, the Definitive Dataset for Real-World Data and the leader in AI Solutions for Precision Oncology. Enterprises integrate Concerto Health AI’s Real-World Data, your data and third-party datasets to drive insights and decision-making across the enterprise.
Concerto Health AI’s Advanced Patient Management Solutions bring patient management to guidelines, precision oncology decision support, and clinical research within a clinic or practise workflow to truly enable precision oncology and value-based care models.
In the show, Brigham will discuss:
What motivated him towards a career in Data Science
What he’s learned throughout his career
How they are applying AI at Concerto Health
3 key areas on how to become a great Data Scientist
Building an effective data science team
How to get involved within the HealthTech sector
Today’s guest is Kenneth Schwartz, VP of Innovation and Analytics at HealthFirst. Healthfirst is a provider-sponsored health insurance company that serves more than 1.4 million members in downstate New York. Healthfirst offers top-quality Medicaid, Medicare Advantage, Child Health Plus, and Managed Long Term Care plans for their customers.
Kenneth is responsible for Healthfirst’s Analytics Delivery, Data Science and Advanced Analytics teams delivering insights that improve the health of New Yorkers. Building capabilities in machine learning, text analytics and graph analysis that combined within a great user experience become first-class Data Products that empower business users throughout the company.
In the show, Kenneth will discuss:
How he transitioned into a career in tech and data science
The interesting work he does at Healthfirst
Challenges of working with legacy data
The benefits they are making to people’s lives
How to make the most out of AI and Data Science in your business
Today’s guest is Gabi Steele, Data Visualization Manager at WeWork in New York City. The focus of Gabi’s work is at the intersection of data storytelling, community building and enterprise innovation. Gabi also co-designed and runs Data Cult, which is an innovative experience which empowers employees to solve real business problems using data.
Gabi leads data visualization and innovation at WeWork, which is the platform for creators, providing hundreds of thousands of members around the world with space, community, and services that enable them to do what they love and create their life’s work. It is their mission is to create a world where people work to make a life, not just a living.
In the show, Gabi will tell you about:
How she became involved in the tech world
Interesting projects she is working on at WeWork
Effectively using your technical skills to improve business decision-making
Improving communication skills
How to get involved in data visualization and storytelling
Advice on how to become successful in your career
Today’s guest is Ainul Huda, who is the Vice President of Analytics, Audience Development and Marketing at Global Media company Condé Nast in New York City. Ainul is an Executive with several years of leadership experience in Data & Analytics, Audience Development & Digital Growth, Strategy, Marketing, Business Planning, Financial Modeling and Operations.
Ainul supports content planning, drives audience growth, engagement & loyalty, as well as helping to maximize monetization across all of Condé Nast brands and functions. This is achieved through innovative marketing tactics & partnerships, comprehensive analysis & measurement, as well as supporting content, product & design optimization through recommendations and analytics.
In the show, Ainul will tell you about:
Developing a data-driven culture at Conde Nast
How to show stakeholders the business value of data analytics
The importance of communication skills
Building successful Data Science teams
The pros and cons of working within industry
Helpful tips on standing out in the interview process
Today’s guest is Danti Chen, Head of Applied Data Science and Insights at Weber Shandwick in New York. Danti is responsible for leading the design and implementation of rigorous analytics using advanced data science techniques for client-oriented actionable insights and building out the Weber Shandwick’s analytics function at a global scale.
Weber Shandwick is a leading global communications network that delivers next-generation solutions to brands, businesses and organizations in major markets around the world. Data-led, with earned ideas at the core, the agency deploys leading and emerging technologies to inform strategy, develop critical insights and heighten impact across multiple sectors.
In the episode, Danti will share:
Advice on moving from academia to industry
What she loves about her job
Challenges to be aware of working as a Data Science
How to improve your communication skills
Building a successful data science team
The benefits Weber Shandwick bring to clients
What’s in store for Weber Shandwick in the near future
Today’s guest is Fílip Vítek, Director of Data Science at TeamViewer in Berlin. Founded in 2005, TeamViewer is one of the worldwide leading solutions for desktop sharing and online collaboration over the Internet. They are fully focused on the development and distribution of high-end solutions for online collaboration and communication. A fast start and high growth rates have led to more than 100,000,000 installations available in more than 30 languages in over 100 countries all over the world. Their software is currently available in more than 30 languages. The base technology developed by the company powers TeamViewer’s state-of-the-art high-performance global server network that routes connections based on geolocalization technology.In the episode, Filip will tell you about:
- Who are TeamViewer
- Transitioning from a business career into Data Science
- Bringing Data Analytics into business
- Challenges in applying Data Science within an organisation
- Advice on overcoming challenges and internal politics
- Important hiring trends within Data Science