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Jason Mariasis
VP Digital Products, Channels & CX at Credit One Bank | 40 Under 40 | Top 100 Innovator & Entrepreneur | Angel Investor
Jason Mariasis: Vice President of Digital Product Management at Credit One Bank
Jason Mariasis is the Vice President of Digital Product Management at Credit One Bank, where he is responsible for leading digital product strategy and digital transformation initiatives.12 He is a results-driven entrepreneur, human-centered product leader, and 40 Under 40 recipient.1
Some key facts about Jason Mariasis:
- He has over 15 years of experience in entrepreneurship and product leadership roles2
- Prior to Credit One Bank, he co-founded Stratus, a company working to make great financial advice accessible4
- He was featured in the New York Times while in college for his entrepreneurial achievements2
- He has been recognized as a 40 Under 40 Business Elite and Top 100 Innovator & Entrepreneur12
- He is passionate about simplifying banking and helping customers succeed at every part of their financial journey3
In his current role at Credit One Bank, Jason leads digital product strategy and oversees exceptional product, design, research, and engineering teams.23 His goal is to help the company expand beyond a credit card provider to a financial success partner that helps customers achieve their goals.2
Highlights
I’m thrilled to announce that I’ve successfully completed the Applied Data Science Program: Leveraging AI for Effective Decision-Making from MIT Professional Education.
This intensive 4-month journey demanded over 25 hours of weekly dedication, pushing me to sharpen my statistics, linear algebra, linear and logistic regressions, and Python programming skills, while ensuring a profound grasp of theory and application in real-world business.
The curriculum was comprehensive, diving into: -Programming in Python --Pandas, NumPy, Matplotlib, Scikit-learn, Tensorflow, Keras, etc -Exploratory Data Analysis & Visualization -Machine Learning --Unsupervised Learning (PCA, t-SNE, K-Means, DBSCAN, GMM, Graph Network Models) --Supervised Learning (Regression, Bootstrapping, Classification, LDA, QDA, Logistic Regression) -Practical Data Science --Forecasting & Time Series --Decision Trees --Bagging --Random Forest --XGBoost -Deep Learning --Artificial Neural Networks --Graph Neural Networks --Convolutional Neural Networks (Computer Vision) --Transfer Learning -Recommendation Systems
Some notable projects and business case reports: -Data cleaning and pre-processing based on statistical insights from an exploratory analysis of raw datasets. -Building algorithms to automate regression analysis and plugging that into a predictive pricing model for the housing market. -Feature extraction and visualization of varied correlative relationships through principal component analysis and t-distributed stochastic neighbor embedding. -Proposing a marketing campaign strategy through predictive analytics built on top of algorithms benchmarked by silhouette score. -Optimizing customer experience on a platform through algorithmic clustering and segmentation. -Using dimensionality reduction to present a case for entering a new market through the introduction of a new product with overlapping features. -Exploring the anatomy and applications of artificial, convolutional, and recurrent neural networks. -Implementing density-based spatial clustering to scale model performance by eliminating noisy data needlessly clustered by outlier-sensitive algorithms. -Evaluating models via train-test splits; cross-validating models with k-folds; training models via bootstrapping - to better identify brain tumors, classify chest x-rays, predict loan defaults, and recommending movies. -Detecting associations in criminal networks through social network analysis to determine which criminal to target first.
A heartfelt thank you to the esteemed MIT professors, industry mentors, and peers who were pillars of this challenging yet inspiring journey.
Excited to continue this learning journey in a world where outsized value creation will increasingly take place at the crossroads of digital product management and advanced analytics.
Thank you to those who came to my session at CCW Las Vegas this year! In the spirit of continuing the conversations that we had onsite, I wanted to share the 2023 – 2024 Customer Contact Executive Benchmarking Report, put together by CMP Research. You can view it here: https://bit.ly/46nPlFO Given the state of the industry, it’s not a surprise that these are the key takeaways:
- Creating a frictionless CX and retaining talent are the top priorities
- Managing technology transitions is the third most urgent priority
- More than 3/4 of executives plan to increase investment in customer facing technologies #CMPResearch #CustomerManagementPractice #CustomerContact
