Product Manager in Athens, Greece

AI/ML/computer vision/big data (automotive): This is a complete machine vision/image processing/3D vision-based metrology product, based on cloud-of-point processing.

In addition, the solution includes a contemporary self-adaptive robot thermal compensation/absolute accuracy product and a standalone 3D vision-based metrology library (grayscale, stereo, laser projection, fringe projection).

The system was installed, among others, at Fiat (Pernambuco, Brazil) and Jaguar Land Rover (UK).

Secuity/ML/big data (M&A): During the due diligence of a software product or company acquisition, the technology stack and software quality and license compliance are analyzed and reported. Additionally, maintenance, risk mitigation, and refactoring costs are automatically calculated, based on a build-in big data analysis platform.

This is a SaaS product deployed on AWS that offers technology stack analysis, third-party and OSS licenses, compliance assessment, building process analysis, and a plan for the virtualization of the product (migration to AWS cloud).

AI/ML/big data (fintech): AMLS ensures maximum coverage and high alerts yield.

Transaction monitoring: AMLS provides secondary scoring of the transaction monitoring process. The approach uses our proprietary semi-supervised technique which is based on a combination of multi-dimensional unsupervised techniques, network analysis, and supervised learning to detect complex money laundering structuring mechanisms.

Screening: AMLS provides secondary scoring of the screening process. The approach uses our proprietary multilayered supervised techniques that combine approaches in improved matching techniques (handles typos, spelling errors, titles, prefix/suffix, etc.) and detailed analysis of secondary information obtained either from internal sources or externally available sources.

G-Guide systems provide unique, innovative solutions for every automated application, from basic de-racking operations to iterative roof panel insertions to complex phased door and closure assemblies.

Return on investment and system value:
• Optimize overall assembly quality and fit
• Employ leading-edge assembly techniques
• Reduce the number of vehicles requiring rework
• Automate hazardous tasks
• Reduce the manpower dedicated to assembly operations
• Reduce the number of materials dispensed
• Eliminate precision mechanical fixturing costs
• Accommodate part and process variation

$200+ million in revenue, more than 300 installations (Ford, Daimler, Audi, Daimler, Nissan, BMW, Tesla, Hyundai, Fiat, JLR, etc.)

AI/ML/computer vision/ big data (automotive):G-Verify: Build Verification and Validation

Bumper-to-bumper inspection and validation.

Thumbs-up for production quality based on quality assurance big data analysis, Ever-increasing expectations for vehicle customization has resulted in a myriad of complex options packages and specialized features. G-Verify solutions provide objective, reliable confirmation that all of your customer’s expectations have been successfully met.

G-Verify can be configured to work in any area of an industrial production facility:
• Bodyshop, paint shop, final assembly, moving line, stop-station
• Utilize various sensor resolutions, standoffs, illumination styles, color or gray-scale, NIR, LED, fluorescent, algorithm types, and much more to personalize a robust and reliable solution. Highly flexible, the G-Verify solution can be easily integrated into your existing production lines.

G-Verify systems offer economical and effective solutions for frame manufacturers—automatically check hundreds of holes and slots in a matter of seconds.

AI/ML/big data (fintech): Tookitakis' Shared Typologie Framework is an innovative machine learning/AI approach anti-money laundering technology. A universal cloud-based repository of anti-money laundering patterns (typologies) is automatically detected or manually compiled. It provides the ability to analyze patterns of AML criminality detected by the third party without violating PII regulations, using a data model-agnostic glass box approach. The framework mitigates the risk implied by new ML techniques.

Tech stack: AWS, Scala, Python, React