SocialSurge Marketing

Senior SEO Specialist

Digital Marketing Specialist

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WorldPantry.com

Marketing Associate

Sellars Absorbent Materials

Purchasing Agent II

Logistics Intern

Charter Communications

Warehouse Worker

Jimmy's Grotto

Line Cook

Lake Ripley Country Club

Dishwasher

Marketing • SEO • Progress Journal Podcast #ProgressNotPerfection

I was not voted Most Likely to Succeed in high school. I don't think my name would've even been on the ballot. After a few life situations early on, I learned life was way too short. This translated to the mentality of, "party hard, have fun, and live life with no regrets."

As I started to realize my life path was going in the wrong direction, and fast, my mentality around how I wanted my life to play out changed.

After realizing I needed to turn my life around, I buckled down. I've used my past experience of being pushed/coached in sports, and have translated that into a drive to explore, create, and build. I am driven to continually learn from what I experience, apply what I have been taught, and add value whenever I can.

My old thought of "no regrets"  has translated to:

1. 𝘞𝘰𝘳𝘬 𝘩𝘢𝘳𝘥 𝘯𝘰𝘸, 𝘢𝘯𝘥 𝘴𝘦𝘵 𝘺𝘰𝘶𝘳𝘴𝘦𝘭𝘧 𝘶𝘱 𝘧𝘰𝘳 𝘵𝘩𝘦 𝘭𝘰𝘯𝘨 𝘳𝘶𝘯.

2. 𝘈𝘱𝘱𝘳𝘦𝘤𝘪𝘢𝘵𝘦 𝘵𝘩𝘰𝘴𝘦 𝘸𝘩𝘰 𝘩𝘢𝘷𝘦 𝘩𝘦𝘭𝘱𝘦𝘥 𝘺𝘰𝘶 𝘢𝘭𝘰𝘯𝘨 𝘵𝘩𝘦 𝘸𝘢𝘺. 𝘋𝘰 𝘺𝘰𝘶𝘳 𝘣𝘦𝘴𝘵 𝘵𝘰 𝘳𝘦𝘵𝘶𝘳𝘯 𝘵𝘩𝘦 𝘧𝘢𝘷𝘰𝘳 𝘢𝘯𝘥 𝘣𝘦 𝘢 𝘭𝘪𝘨𝘩𝘵 𝘵𝘰 𝘴𝘰𝘮𝘦𝘰𝘯𝘦 𝘦𝘭𝘴𝘦.

3. 𝘓𝘪𝘷𝘦 𝘭𝘪𝘧𝘦 𝘸𝘪𝘵𝘩 𝘯𝘰 𝘳𝘦𝘨𝘳𝘦𝘵𝘴......𝘴𝘵𝘪𝘭𝘭.

𝗜 𝗱𝗼 𝗻𝗼𝘁 𝗹𝗶𝘃𝗲 𝗮 𝗹𝗶𝗳𝗲 𝗯𝗮𝘀𝗲𝗱 𝗼𝗻 𝗽𝗼𝗽𝘂𝗹𝗮𝗿𝗶𝘁𝘆, 𝗯𝘂𝘁 𝗼𝗻𝗲 𝗼𝗳 𝘃𝗮𝗹𝘂𝗲𝘀 𝗮𝗻𝗱 𝗶𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆. 𝗜 𝘄𝗼𝗿𝗸 𝘁𝗼 𝗿𝗲𝗹𝗮𝘆 𝘁𝗵𝗶𝘀 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝘄𝗶𝘁𝗵𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝘁𝗵𝗮𝘁 𝗜 𝗽𝗼𝘀𝘁 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀 𝗜 𝗵𝗮𝘃𝗲.

You can learn more about what I do at: https://www.thomasciampa.com

Thomas Ciampa

General Motors

Responsible for MLOps Strategy & Execution which encompasses:

Building and deploying complex AI models in Autonomous driving

Developing infrastructure and pipelines to scale for massive datasets

Working with cutting-edge tools and technologies such as Databricks, Delta Lake-house, Pyspark TorchDistributor, Deltatorch, etc.

Selected work:
1. Implementing and scaling Computer Vision Object classification, detection & segmentation for multi-GPU & multi-node training. Implementing best practices for production.

2. Designing & implemeting a hybrid cloud model training + on-prem inferencing on NVIDIA Triton utilizing a shared MLFlow server.

3. Developing a scalable Pyspark pipeline to process massive telemetry data to rasterize into images and create road & lane edges

AI - ML Specialist

Abacus.AI

Led multiple use-cases, POCs & implementations of state-of-the-art Neural Network models - Doing what it takes. Currently advisor.

Advisor

1618.ai

AI Solutions: Building advanced Machine Learning solutions while Keeping-It-Super-Simple.

Consulting Services: Pre & Post-sales / Delivery / PM (Agile/Scrum/Kanban)

Advisory: Bringing close to 2 decades of extensive & diverse experience in SWE, Consulting, teaching and advising C-level at multi-national companies.

Advanced Machine Learning / Image analytics / Deep Learning
Data pipelines - Spark/Hadoop/Hive & performance tuning
Data Analysis / Feature Engineering / Business Intelligence

Principal AI / Machine Learning Practitioner

DataRobot

Leading customer support in AI, Auto-ML, Time Series, MLOps & API/Automation.

Primarily working with clients on developing use cases, determining ROI, Proofs-of-Concept, rapid prototyping & delivery, customization via API, deployments & maintenance using MLOps among other responsibilities.

Lead Data Scientist

Leading & managing multiple distributed/global teams in implementing Data Science solutions:
• Advanced Statistical / Machine Learning Models of various complexities 
• Attribution analysis / BI / Visualization
• End-to-end projects

Supporting other functions in the consulting practice:
• Product & Solutions Pre-sales
• Client Advisory & Enablement (teaching)
• Project Management

Selected Models (Multiple industries):
• Deep Learning - Image classification (CNN), NLP, Anomaly detection (Auto-encoders).
• GLM, GBM, Neural Networks, Stacked Ensembles

Selected Models (Financial):
• Parametric survival (Hazard-rates) & Vasicek, Logistic regression, Fractional Logit, Linear regression/ARIMA

Data Science Consulting Lead - Manager

Wells Fargo

Enterprise Market Risk - Counterparty Credit Risk Analytics involving Potential Future Exposure (PFE) and Regulatory projects (Basel, CCAR), Market Risk Analytics involving VaR & Greeks. Led Quantitative analysis/delivery and Machine Learning projects.

Selected Project work:
• Models in open-source H2O platform (GBM, GLM, etc.)
• Profile Based Reserve - This is a simplified version of Credit Valuation Adjustment (CVA) - we determine the potential positive exposure of a counterparty using Monte Carlo simulations and calculate the 2-week margin required to mitigate the maximum expected losses.
• Incorporation of Collateral / CSA into the Potential Future Exposure (PFE) calculations.
• Enhancements to Market Risk VaR calculations for various products (FX, Securities Trading & Financing, etc.)

Independent Consultant

I - Corporate Investments Group

• Sr Quantitative Developer / Analyst supporting FAS Interest Rate Derivatives Hedging for CIG:

Led implementation of switch to Dual Curve / Standard CSA discounting for Fixed Income assets (UST, CMBS and RMBS) and hedge instruments (Swaps, TBA pools). Involves multi-step mathematically complex calculations in arriving at daily basis adjustments posted to G/L.

Enhanced Attribution Analysis of Fixed Income Products and Derivatives to understand how much of the daily Basis Adjustments are atrributed to each contributing factor (rates, time, roll, cashflows)

Applied Machine Learning techniques in Interest Rate (IR) curve, Bond price and pre-payment models.
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II - Enterprise Credit Risk Analytics - Moody's RiskFrontier, Moody's KMV Model, Monte Carlo Simulation, Portfolio Optimization, CVA

• Lead Quantitative Consultant working with Moody’s RiskFrontier - in-depth analysis / prototyping required for consumer and commercial portfolios and segmentation. 

In-depth analysis and implementation of Monte-Carlo Simulation to solve problems found like variance in EL and CVAR between Portfolio and Instrument levels. Evaluated and provided feedback on vendor tool.

Implemented Machine Learning in the Retail data processes such as K-means clustering and pooling.

• Contributed to In-house built Portfolio Optimization module with metrics like optimized Expected Loss and Conditional Value at Risk (CVAR) at Optimization Segment level.

Senior Quantitative Analytics Consultant

AI leader - practitioner with over 10 years experience spanning analytical, managerial, sales and teaching roles in AI. See featured items for examples of high ROI projects I implemented.

Extensive experience in building & implementing ML in Production and Consulting (Delivery, pre/post-sales and customer success).

My passion is in applying AI to solve complex business problems by building highly efficient and scale-able solutions. To achieve this, I combine strong analytical skills with subject matter expertise and a * client-focused * consultative mind-set. 

Quick learner - enjoy deep analytical work and collaboration equally. The customer and the team always come first in my books  - lead from the ground-up, with a "let's get it done" motto. 

* Radically open-minded - highly collaborative - results oriented *

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* If you think we should connect, please send an invite. I'm a radically open-minded life-long student and am yet to meet someone I didn't learn something from. *
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Machine Learning / AI - Regression, Classification, GLM, RF, GBM, XGBoost, SVM, Deep learning (MLP, CNN, RNN), Clustering, PCA, Anomaly detection, Collaborative filtering, Reinforcement learning, Advanced Concepts and fundamental knowledge (Calculus, OR, Statistics, etc.)

Tools: Python ecosystem, Pytorch, Lightning, HuggingFace, Databricks, Pyspark, h2o, BI tools, advanced SQL, etc.

Leadership, Scrum / Agile
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taplio

The Battle

Thomas Ciampa

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