In this episode of Mining Your Own Business, Data Scientist Xhoana Laska shares how she and her team are bringing data innovation to the field of industrial paint and coatings, an industry that became prominent in the late 1800s.

With her background in mathematics and statistics, Xhoana’s knack for numbers has come in handy in her role at National Coatings & Supplies | Single Source, Inc. She has spearheaded projects to save thousands of labor hours, optimize inventory processes, improve demand forecasting, and more.

Join us as our podcast host, Evan Wimpey, chats with Xhoana about interesting projects she’s worked on and insight she’s gained along the way!

In this episode you will learn:

⛛ The importance of identifying areas where data analysis can drive significant efficiency improvements
⛛ Why effective communication is crucial for stakeholder buy-in
⛛ The need to prioritize projects based on business-critical needs
⛛ The importance of creating a culture of learning that empowers employees

Quote
💬 “I enjoy working on problems that involve bringing solutions that can potentially save money or optimize and be efficient at the end of the day.”

Featured in This Episode

Xhoana Laska, Data Scientist, National Coatings & Supplies | Single Source, Inc.
From process optimization to demand forecasting, Xhoana Laska enjoys creating data-driven solutions for complex business problems. And that’s at the heart of her work as a data scientist for National Coatings & Supplies | Single Source, Inc. (NCS SSI).

With over three years of experience in the field, Xhoana has a knack for numbers and strong background in mathematics. She specializes in business process automation and statistical and machine learning modeling for procurement, sales, and marketing. She’s also a proud member of the Wolfpack at NC State University, where she received her Master of Statistics degree.

LinkedIn: linkedin.com/in/xhoana-laska

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Introduction
00:50 Xhoana shares her journey into the field of data science.
01:56 Evan shifts the conversation to discuss Xhoana’s first project at NCS SSI.
06:31 Evan discusses the importance of stakeholder involvement in the project.
07:27 Xhoana explains the support provided by the IT team for data quality and accessibility.
10:08 Evan and Xhoana discuss data quality and tools used at NCS SSI.
13:41 The discussion shifts to the process of prioritizing projects at NCS SSI.
22:17 Evan invites Xhoana to share her ideas for future data science projects.
25:33 Evan wraps up the conversation with Xhoana.

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

Explore the dynamic world of retail data analytics with Sravan Vadigepalli, Senior Director of Products and Engineering at Lowe’s. In this episode you’ll learn about the unique analytics challenges and opportunities in the home improvement space and how Lowe’s approaches product development.

During the chat Sravan also shares his thoughts on the future of data-driven innovation in retail. Grab some coffee and join host Evan Wimpey as he delves into the intersection of technology and customer-centric solutions. We hope you enjoy the conversation!

In this episode you will learn:

⛛ The importance of recognizing and adapting to the diverse needs of customers
⛛ Why data initiatives should be aligned with broader business objectives
⛛ How Sravan’s team uses a unique framework to streamline decision-making processes
⛛ The need for a balance between building internal tools and leveraging external solutions

Quote
💬 “For data folks like us, you need to get into the weeds of the business.”

Featured in This Episode

Sravan Vadigepalli, Senior Director of Products and Engineering, Lowe’s
Sravan Vadigepalli has spent the past decade building and curating data analytics teams in the retail industry. He specializes in translating data into insights and applications of Machine Learning/AI models to the ever-evolving retail space. Sravan did his MS in MIS from Oklahoma State University and an MBA from the University of Illinois Urbana-Champaign. Outside of work, Sravan is a self-proclaimed long-distance endurance runner.
LinkedIn: linkedin.com/in/sravanvadigepalli/

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Introduction of the podcast and the guest, Sravan Vadigepalli.
00:45 Sravan Vadigepalli shares his background and career path.
02:53 Discussion on the differences in data challenges between various retail sectors.
8:24 Discussion on the process of developing data products and analytic products.
12:52 Explanation of the prioritization process for projects.
15:49 Discussion on the frameworks used for project prioritization.
19:31 Conversation shifts to evaluating internal versus external solutions for product development.
22:17 Sravan shares some ideas for the future.
25:10 Evan wraps up the show.

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

When considering evaluation metrics for classification models, is it possible for one metric to rule them all? Join us for a lively debate between Aric LaBarr, Associate Professor of Analytics at NC State's Institute for Advanced Analytics, and Robert Robison, Elder Research Senior Data Scientist.

During the debate Robert champions AUC’s comprehensive measure of model performance, while Aric advocates for a broader perspective, emphasizing the importance of business context in metric selection. Tune in as host Evan Wimpey moderates the discussion, and gain valuable insight on what really matters when it comes to machine learning model evaluation. We hope you enjoy the conversation!

In this episode you will learn:

⛛ The importance of exploring various metrics to evaluate model performance

⛛ Why metrics should align with business objectives

⛛ The need for data science teams to invest time in feature engineering

⛛ Why a model's success relies not only on its performance but also on stakeholders' ability to understand and trust the insights it provides

Quotes
💬 “There's a difference between communicating the value of a model and distinguishing between which models are better.” –Robert Robison

💬 “If you can't explain the model to your stakeholders or business users, then it's not going to get implemented.” –Aric LaBarr

Featured in This Episode

Aric LaBarr | Associate Professor of Analytics, Institute for Advanced Analytics

LinkedIn: https://www.linkedin.com/in/ariclabarr/

Robert Robison | Senior Data Scientist, Elder Research

LinkedIn: https://www.linkedin.com/in/robert-robison/

Evan Wimpey, Director of Analytics Strategy, Elder Research

LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Evan introduces the debate topic and guests, Aric LaBarr and Robert Robison.
01:37 Robert begins his argument by defining AUC (Area Under the Curve) and its significance as a metric for classification models.
06:11 Aric begins his rebuttal, challenging the notion that AUC is the only metric to consider.
09:26 Robert provides a rebuttal to Aric's points.
11:48 Aric starts his rebuttal, focusing on communicating models to business users.
14:41 Robert responds to Aric’s points.
16:18 Evan asks Robert if certain cases may require metrics other than AUC.
17:03 Robert responds to Evan’s question.
17:53 Aric weighs in on the question.
19:37 Evan asks Aric if focusing solely on AUC may save time and costs.
20:30 Aric responds to Evan’s question.
22:20 Evan gives time for the debaters to ask each other questions.
25:30 The debaters share closing remarks, summarizing their positions.
29:14 Evan wraps up the show.

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/