Bill Franks, Chief Analytics Officer, Teradata, presents at the 2012 Big Analytics Roadshow.
As enterprises come to understand the value of analytics, more support and funding is being allocated to build these departments. Managers are now faced with the challenge of who to hire. What exactly makes a great analytic professional? Is a Data Scientist a "must have"? Should a candidate have a PhD? Is prior experience in a specific industry vital? Just what is the right fit when creating a successful team? The answers to these questions are still unclear as the value of analytics continues to grow.
In this session, Bill Franks, author of the book, Taming the Big Data Tidal Wave, addresses these and many more questions as he defines the characteristics of high-performing data scientists and great analytics teams.
The 5 People in your Organization that grow Legacy CodeRoberto Cortez
Have you ever looked at a random piece of code and wanted to rewrite it so badly? It’s natural to have legacy code in your application at some point. It’s something that you need to accept and learn to live with. So is this a lost cause? Should we just throw in the towel and give up? Hell no! Over the years, I learned to identify 5 main creators/enablers of legacy code on the engineering side, which I’m sharing here with you using real development stories (with a little humour in the mix). Learn to keep them in line and your code will live longer!
Razorfish Multi-Channel Marketing: Better Customer Segmentation and TargetingTeradata Aster
Matt Comstock, Vice President Business Intelligence Office, Razorfish, presents at the Big Analytics 2012 Roadshow.
From search to email to social, customers are interacting with your brand across a variety of channels. But what do people do once they view an advertisement or get an email? What common behaviors are displayed once they’re on your site? By combining media exposure/behavior, site-side media, and in-store purchase data, you can understand better the impact media has on driving value to your business. Come to this session to learn how better data-driven multi-channel analysis lets you see what consumers do before they become a customer to understand what content influences which segments of users by media audience. Discover new segmentation and targeting strategies to improve engagement with your brand and increase advertising lift. See how a leader in digital marketing uses a combination of technologies including Teradata Aster, Hadoop, and Amazon Web Services to handle big data and provide big analytics to improve business value.
Using SQL-MapReduce for Advanced AnalyticsTeradata Aster
Industry analyst Rick van der Lans explains how Aster Data's patent-pending SQL-MapReduce programming framework makes new types of analytic queries possible. The main benefits he outlines are: Parallelization of complex operations; Simplification of queries; Predictabile query performance; Efficient data access; and Linear scalability.
Check out Rick's complimentary research report at http://www.asterdata.com/ar_SQL-MapReduce_for_Advanced_Analytics/, in which he provides a very clear technical explanation of SQL-MapReduce and its analytic application use cases.
Product Management in the Era of Data ScienceMandar Parikh
My slide-deck from a webinar on the same topic for the Institute of Product Leadership, April 4th, 2017
What does it take to build killer products in the “AI-first” era? What makes for a great Data Science-driven product and how do great Product Managers leverage Data Science to drive value for customers? Find out how to avoid the pitfalls of hype-chasing Data Science tactics. Learn how to work with Data Science and Engineering to build a compelling product and solve real problems.
Mandar takes a practitioner’s approach to present his recipe for success for building Data Science-driven products that drive enduring value for customers.
The 5 People in your Organization that grow Legacy CodeRoberto Cortez
Have you ever looked at a random piece of code and wanted to rewrite it so badly? It’s natural to have legacy code in your application at some point. It’s something that you need to accept and learn to live with. So is this a lost cause? Should we just throw in the towel and give up? Hell no! Over the years, I learned to identify 5 main creators/enablers of legacy code on the engineering side, which I’m sharing here with you using real development stories (with a little humour in the mix). Learn to keep them in line and your code will live longer!
Razorfish Multi-Channel Marketing: Better Customer Segmentation and TargetingTeradata Aster
Matt Comstock, Vice President Business Intelligence Office, Razorfish, presents at the Big Analytics 2012 Roadshow.
From search to email to social, customers are interacting with your brand across a variety of channels. But what do people do once they view an advertisement or get an email? What common behaviors are displayed once they’re on your site? By combining media exposure/behavior, site-side media, and in-store purchase data, you can understand better the impact media has on driving value to your business. Come to this session to learn how better data-driven multi-channel analysis lets you see what consumers do before they become a customer to understand what content influences which segments of users by media audience. Discover new segmentation and targeting strategies to improve engagement with your brand and increase advertising lift. See how a leader in digital marketing uses a combination of technologies including Teradata Aster, Hadoop, and Amazon Web Services to handle big data and provide big analytics to improve business value.
Using SQL-MapReduce for Advanced AnalyticsTeradata Aster
Industry analyst Rick van der Lans explains how Aster Data's patent-pending SQL-MapReduce programming framework makes new types of analytic queries possible. The main benefits he outlines are: Parallelization of complex operations; Simplification of queries; Predictabile query performance; Efficient data access; and Linear scalability.
Check out Rick's complimentary research report at http://www.asterdata.com/ar_SQL-MapReduce_for_Advanced_Analytics/, in which he provides a very clear technical explanation of SQL-MapReduce and its analytic application use cases.
Product Management in the Era of Data ScienceMandar Parikh
My slide-deck from a webinar on the same topic for the Institute of Product Leadership, April 4th, 2017
What does it take to build killer products in the “AI-first” era? What makes for a great Data Science-driven product and how do great Product Managers leverage Data Science to drive value for customers? Find out how to avoid the pitfalls of hype-chasing Data Science tactics. Learn how to work with Data Science and Engineering to build a compelling product and solve real problems.
Mandar takes a practitioner’s approach to present his recipe for success for building Data Science-driven products that drive enduring value for customers.
Huntel global webinar aligning data talent with your analytics needsHuntel Global
Learn about the importance of data, analytics, and talent search. We'll explore the answers to:
• Where are you along the analytics continuum?
• Do you have a plan to getting the most out of your mountain of data?
• Do you know what questions you want to answer and what metrics will drive the answers?
• Have you ever had trouble with finding the right talent for your data analytics objective or initiative?
• Where do you go for help?
SourceCon Atlanta 2013 Presentation: How to Hire and Build Your Own Sourcing ...Glen Cathey
This is my 2013 SourceCon Atlanta presentation on how to hire and grow your own sourcing team. It covers my hiring profile, a few Boolean search strings for finding people who fit my hiring profile, support for my theory that you can create super sourcers (and recruiters for that matter) by hiring people with no experience and training them properly, coming from the book "The Talent Code." It also explores the pros and cons of hiring experienced sourcers vs. hiring people with no experience and building sourcers from scratch.
How Intercom built ‘Fin’, a GPT-4 powered chatbot_Fergal Reid_UXDX_EMEA_2023UXDXConf
Join Fergal as he shares how they developed ‘Fin’, a chatbot that actually solves up to 50% of support questions. This session will shed light on the product development process of Fin, the challenges encountered, and the opportunities it brought forth. The talk will encompass Intercom’s experiences and lessons learned from integrating large language models in a live production environment.
Kdd 2019: Standardizing Data Science to Help HiringGreg Makowski
Initiative for Analytics and Data Science Standards (IADSS) workshop presentation at the ACM KDD conference (Association of Computing Machinery Knowledge Discovery in Databases).
Bit by Bit: Effective Use of People, Processes and Computer Technology in the...Jack Pringle
A somewhat updated attempt to offer some practical tips for attorneys in managing technology, change management, process improvement, and many other buzzwords
Gayatri Patel, eBay, presents at the Big Analytics 2012 Roadshow
The wonders of what data can do for an organization is measured in the productivity and competitiveness of their team's decisions. Some believe more data is the key. Agreed...but good decisions require more than just deriving intelligence from big data. In this dynamic market, the need to socialize and evolve ideas with other teams, quickly correlate information across sources, and test ideas to fail fast early are strong enablers to gain competitive footing. eBay¹s analytic and technology advancements garners insights and approaches that continue to help our employees tell their "data stories" and make better decisions.
Using Data to Manage in Today’s Chaotic EnvironmentTeradata Aster
DJ Patil, Data Scientist, Greylock Partners, presents at the Big Analytics 2012 Roadshow in San Francisco.
The ability to manage and leverage data has never been more critical to business. At the same time, the volume and types of data have grown dramatically in the past few years. The choices for technologies, people, and processes are complex. In this keynote session, Dr.DJ Patil will talk about how to manage through all this chaos.
Huntel global webinar aligning data talent with your analytics needsHuntel Global
Learn about the importance of data, analytics, and talent search. We'll explore the answers to:
• Where are you along the analytics continuum?
• Do you have a plan to getting the most out of your mountain of data?
• Do you know what questions you want to answer and what metrics will drive the answers?
• Have you ever had trouble with finding the right talent for your data analytics objective or initiative?
• Where do you go for help?
SourceCon Atlanta 2013 Presentation: How to Hire and Build Your Own Sourcing ...Glen Cathey
This is my 2013 SourceCon Atlanta presentation on how to hire and grow your own sourcing team. It covers my hiring profile, a few Boolean search strings for finding people who fit my hiring profile, support for my theory that you can create super sourcers (and recruiters for that matter) by hiring people with no experience and training them properly, coming from the book "The Talent Code." It also explores the pros and cons of hiring experienced sourcers vs. hiring people with no experience and building sourcers from scratch.
How Intercom built ‘Fin’, a GPT-4 powered chatbot_Fergal Reid_UXDX_EMEA_2023UXDXConf
Join Fergal as he shares how they developed ‘Fin’, a chatbot that actually solves up to 50% of support questions. This session will shed light on the product development process of Fin, the challenges encountered, and the opportunities it brought forth. The talk will encompass Intercom’s experiences and lessons learned from integrating large language models in a live production environment.
Kdd 2019: Standardizing Data Science to Help HiringGreg Makowski
Initiative for Analytics and Data Science Standards (IADSS) workshop presentation at the ACM KDD conference (Association of Computing Machinery Knowledge Discovery in Databases).
Bit by Bit: Effective Use of People, Processes and Computer Technology in the...Jack Pringle
A somewhat updated attempt to offer some practical tips for attorneys in managing technology, change management, process improvement, and many other buzzwords
Similar to What Makes A Great Data Scientist? (20)
Gayatri Patel, eBay, presents at the Big Analytics 2012 Roadshow
The wonders of what data can do for an organization is measured in the productivity and competitiveness of their team's decisions. Some believe more data is the key. Agreed...but good decisions require more than just deriving intelligence from big data. In this dynamic market, the need to socialize and evolve ideas with other teams, quickly correlate information across sources, and test ideas to fail fast early are strong enablers to gain competitive footing. eBay¹s analytic and technology advancements garners insights and approaches that continue to help our employees tell their "data stories" and make better decisions.
Using Data to Manage in Today’s Chaotic EnvironmentTeradata Aster
DJ Patil, Data Scientist, Greylock Partners, presents at the Big Analytics 2012 Roadshow in San Francisco.
The ability to manage and leverage data has never been more critical to business. At the same time, the volume and types of data have grown dramatically in the past few years. The choices for technologies, people, and processes are complex. In this keynote session, Dr.DJ Patil will talk about how to manage through all this chaos.
This data is from registrants for the Big Analytics 2012 events. The survey asked participants to classify themselves as “business” or “IT”.
Survey details:
Number of survey respondents and date -
San Francisco (April) = 507
Boston (May)= 322
Chicago (June) = 441
New York (Dec) = 894
TOTAL = 2164
Practical Applications of Visual AnalyticsTeradata Aster
Dustin Smith, Community Manager, Tableau Software, presents at the 2012 Big Analytics Roadshow.
Organizations now have the ability to store and process massive amounts of data like never before. And there are huge expectations for turning data into a fundamental driver for business transformation and competitive advantage.
Visual analytics is helping everyday employees gain insight into data in order to solve unexpected problems and challenges, it is changing the way people interact with data and the way business intelligence is defined in organizations. In this presentation, we will share real-world examples of how everyday people can and are using visual analytics to solve some of businesses most challenging issues.
Trust and Influence in the Complex Network of Social MediaTeradata Aster
William Rand, University of Maryland, presents at the 2012 Big Analytics Roadshow.
The dramatic feature of social media is that it gives everyone a voice; anyone can speak out and express their opinion to a crowd of followers with little or no cost or effort, which creates a loud and potentially overwhelming marketplace of ideas. The good news is that the organizations have more data than ever about what their consumers are saying about their brand. The bad news is that this huge amount of data is difficult to sift through. We will look at developing methods that can help sift through this torrent of data and examine important questions, such as who do users trust to provide them with the information and the recommendations that they want? Which tastemakers have the greatest influence on social media users? Using agent-based modeling, machine learning and network analysis we begin to examine and shed light on these questions and develop a deeper understanding of the complex system of social media.
Mohanbir Sawhney, Robert R. McCormick Tribune Foundation Clinical Professor of Technology Kellogg School of Management, Northwestern University presents at the 2012 Big Analytics Roadshow.
Companies are drinking from a fire hydrant of data that is too big, moving too fast and is too diverse to be analyzed by conventional database systems. Big Data is like a giant gold mine with large quantities of ore that is difficult to extract. To get value out of Big Data, enterprises need a new mindset and a new set of tools. They also need to know how to extract actionable insights from Big Data that can lead to competitive advantage. The Big Story of Big Data is not what Big Data is, but what it means for business value and competitive advantage.... read more: http://www.biganalytics2012.com/sessions.html#mohan_sawhney
Big Brands Meet Big Data – The Newest Innovator’s DilemmaTeradata Aster
Marc Parrish, Vice President, Retention & Loyalty Marketing, Barnes & Noble, presents at the 2012 Big Analytics Roadshow.
Big Data is moving too fast for Big Brands. They don't have the ability to technically pivot, to move quickly enough to take advantage of the astounding amount of customer information that's available, and make it part of their everyday practices. This poses a great risk to the world’s great retailers. Well-managed companies often fail because the very same management practices that made them industry leaders also make it difficult to assimilate the disruptive technologies that in the end allow others to steal their market.
With Big Data, the gap between merely sustaining your operations, and adopting disruptive technologies, is the difference between progress, or perish.
Simplifying Big Data Analytics for the BusinessTeradata Aster
Tasso Argyros, Co-Founder & Co-President, Teradata Aster presents at the 2012 Big Analytics Roadshow.
The opportunity exists for organizations in every industry to unlock the power of iterative, big data analysis with new applications such as digital marketing optimization and social network analysis to improve their bottom line. Big data analysis is not just the ability to analyze large volumes of data, but the ability to analyze more varieties of data by performing more complex analysis than is possible with more traditional technologies. This session will demonstrate how to bring the science of data to the art of business by empowering more business users and analysts with operationalized insights that drive results. See how data science is making emerging analytic technologies more accessible to businesses while providing better manageability to enterprise architects across retail, financial services, and media companies.
Evaluating Big Data Predictive Analytics PlatformsTeradata Aster
Mike Gualtieri, Principal Analyst, Forrester Research, presents at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012
Presentation title: Evaluating Big Data Predictive Analytics Platforms
Abstract: Great. You have Big Data. Now what? You have to analyze it to find game-changing predictive models that you can use to make smart decisions, reduce risk, or deliver breakthrough customer experiences. Big Data Predictive Analytics solutions are software and/or hardware solutions that allow firms to discover, evaluate, optimize, and deploy predictive models by analyzing big data sources. In this session, Forrester Principal Analyst Mike Gualtieri will discuss the key criteria you should use to evaluate Big Data Predictive Analytics platforms to meet your specific needs.
Keynote: Cross Industry Lessons from Moneyball AnalyticsTeradata Aster
Ari Kaplan keynote presentation at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012
Presentation title: "Cross Industry Lessons from Moneyball Analytics", by Ari Kaplan, "Moneyball" advisor to Major League Baseball teams and President of AriBall
Ari Kaplan is a leading figure in sports analytics. Known throughout the Major Leagues for revolutionizing and modernizing player assessment, Ari's use of analytics and technology helps coaches prepare for games, players understand their strengths and weaknesses, General Managers forecast future performance and risk of player contracts and draft picks, and more.
In this presentation, Kaplan discusses how professional sports teams and players use analytics and data visualization in the Major Leagues. Through his 23 years of experience in over half of all MLB organizations, he will discuss the changes that took place and where analytics will continue to innovate in the future.
Technology Strategies for Big Data Analytics, Teradata Aster
SAS Presentation delivered at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012
Presentation title: Technology Strategies for Big Data Analytics, by Bernard Blais, Global Strategist and Principal Manager, SAS
The exploding volume, complexity and velocity of big data present an increasing challenge to organizations, but also a significant opportunity to derive valuable insights. As organizations are tasked with managing massive data sets, it’s clear that the value of big data will be derived from the analytics that can be performed on it. Analytics is the key to identifying patterns, managing risks and tackling previously unsolvable problems. This presentation provides an overview of how to comprehensively tackle big data, including emerging strategies for information management, analytics, and high performance analytics.
Mastering MapReduce: MapReduce for Big Data Management and AnalysisTeradata Aster
Whether you’ve heard of Google’s MapReduce or not, its impact on Big Data applications, data warehousing, ETL,
business intelligence, and data mining is re-shaping the market for business analytics and data processing.
Attend this session to hear from Curt Monash on the basics of the MapReduce framework, how it is used, and what implementations like SQL-MapReduce enable.
In this session you will learn:
* The basics of MapReduce, key use cases, and what SQL-MapReduce adds
* Which industries and applications are heavily using MapReduce
* Recommendations for integrating MapReduce in your own BI, Data Warehousing environment
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
What Makes A Great Data Scientist?
1. What Makes A Great Data Scientist?
Bill Franks
Chief Analytics Officer, Global Alliances, Teradata
Bill.Franks@Teradata.com
@BillFranksGA www.Bill-Franks.com
www.linkedin.com/in/billfranksga
www.youtube.com/user/billfranksga/videos?view=1
www.tamingthebigdatatidalwave.com
2. The Big Data Tidal Wave Is Coming…
…Will your organization have the right talent to tame it?
2 Confidential and proprietary.
3. Who Is The Data Scientist?
Analyst
Data Scientist
Statistician Advanced
Analytics
Consultant
Predictive
Modeler
Common Question:
Data Miner
Do others share your view of
the similarities?
3 Confidential and proprietary.
4. Data Scientists:
Common Misconceptions Miss The Mark
• It is not just about:
• Programming skills
• Statistics and math skills
• Advanced degrees in relevant fields
• Specific industry experience
• Hire knowledge and skills, not just check boxes!
• Most great analytic professionals are an exception
• Some examples…
Many skills are necessary, but not sufficient
4 Confidential and proprietary.
5. Some Critical, Yet Underrated, Traits Of A
Great Data Scientist
• Commitment
• Creativity
• Business Savvy
• Presentation Skills
• Intuition
Note: The traits are listed in no particular order Common Question:
What about other traits?
5 Confidential and proprietary.
6. Commitment
Traits Of Great Data Scientists (1 of 5)
• Commitment benefits every profession
• People either have it or they don’t
• Don’t waste your time on someone without it
6 Confidential and proprietary.
7. Commitment
Traits Of Great Data Scientists (1 of 5)
Assessing candidates:
• Listen carefully to how a candidate describes their work
• How do they deal with problems?
• Do they go the extra mile?
• Once hired, it is very easy to see if someone has this or not
7 Confidential and proprietary.
8. Creativity
Traits Of Great Data Scientists (2 of 5)
• This is not the first thing most people think about
• Every analytic endeavor is different…
• Every data source has issues…
• There are many ways to frame a problem…
• Need to aim for improvement, not perfection
Common Question:
Aren’t analytics all about
formulas and not creativity?
8 Confidential and proprietary.
9. Creativity
Traits Of Great Data Scientists (2 of 5)
Assessing candidates:
• Creativity is a rare trait in those with the technical skills
• Ask how they dealt with some “Oh #$%@!!!” moments
• A creative person will have a good story, not a list of steps
9 Confidential and proprietary.
10. Business Savvy
Traits Of Great Data Scientists (3 of 5)
• Data Scientists are an odd hybrid
• Strong business and technical skills are required
• Ability to focus on the important is key
• Cultural awareness is critical
• Business savvy ≠ experience
Common Question:
Are there any other examples of
focusing on the important?
10 Confidential and proprietary.
11. Business Savvy
Traits Of Great Data Scientists (3 of 5)
Assessing candidates:
• Ask why they made the decisions they did
• You should hear some practical and business considerations
• If you just hear technical criteria, be wary
11 Confidential and proprietary.
12. Presentation Skills
Traits Of Great Data Scientists (4 of 5)
• Must be able to engage non-technical audiences
• Technical details will lose a business audience
• Results aren’t the most important factor of success
• Why do the results matter & what should be done?
• It is all about storytelling…
12 Confidential and proprietary.
13. Presentation Skills
Traits Of Great Data Scientists (4 of 5)
Assessing candidates:
• Take a test drive: Have them present at the interview
• Ask for articles, white papers, etc.
• Check out their social media presence
• You’ll see exactly where they stand
Common Question:
Do even junior people
need these skills?
13 Confidential and proprietary.
14. Presentation Skills
Traits Of Great Data Scientists (4 of 5)
• Below are actual slides from a candidate presentation
• The person did not get the job…
14 Confidential and proprietary.
15. Intuition
Traits Of Great Data Scientists (5 of 5)
• Very hard to quantify
• Is the right decision usually made the first time?
• Must win trust from business partners
• Analysis requires a lot of art with the science
• Must be a data artist as well as a data scientist!
15 Confidential and proprietary.
16. Intuition
Traits Of Great Data Scientists (5 of 5)
Assessing candidates:
• Hard to list criteria that aren’t too “squishy” for HR
• Ask about background in art, music, or other creative area
• Once hired, you’ll see over time if someone has it
Common Question:
Does artistry imply that two
people will get two answers to
the same problem?
16 Confidential and proprietary.
17. Does Big Data Change Everything?
> No…
> Your fundamental data and analytic strategies
won’t change…
> You may need some new tools and tactics…
> However, the big picture remains:
Driving value from data through effective analytics
The right people will help you tame it!
17 Confidential and proprietary.
18. Great Data Scientists…
• “Get” data
• “Get” the business issues
• “Get” how to frame problems
• “Get” that they are artists as well as scientists
• Will be able to tame big data for you!
18 Confidential and proprietary.