Amir Daaee Email & Phone Number

As the chief data scientist at Zeenome, a leading company specializing in personalized health and longevity solutions, I've been instrumental in harnessing AI and data analytics to advance the longevity industry. My role at Zeenome encompasses:● Model Performance:Developed ML model for all cause mortality prediction (scikit-learn), achieved 0.9 ROC-AUC by employing gradient boosting models and meticulous hyperparameter tuning, resulting in a 10% increase in customer retention due to more effective personal health plans.● Data Processing Efficiency:Scaled data processing capabilities by 3x, ingesting diverse health data sources (EHR, genomics, wearables, blood marker) using Python and Spark. This broadened our insights for comprehensive health and longevity analysis.● Deployment Success Rate:Optimized model deployment pipeline using CI/CD practices (gitlab, DVC, minio), achieving a 95% first-attempt success rate and streamlining model updates for rapid iteration."● Collaboration and Impact on Clinical Decisions:Fostered collaboration between data science and clinical teams, utilizing explainable AI, Graph neural network and self-supervised learning (Pytorch, tensorflow) on cellular pathways to increase clinician trust and adoption by 40%, enhancing personalized health plan precision.● Operational Efficiency in MLops:Revamped MLops practices, cutting deployment times by 50% through containerization and automation (Docker, Kubernetes). Maintained 99.9% model uptime, supporting seamless scaling of our model portfolio.

At Krypto VPN, I played a pivotal role in the development and deployment of a high-performance and stable network of proxies designed to enable users to bypass censorship imposed by governments or ISPs. The system encompassed user management, usage monitoring, and a CMS for user access control. My key contributions and outcomes included:● Infrastructure Scalability and Performance:Enhanced network performance by reducing proxy response times from 800ms to 300ms and implemented HAProxy load balancing for TLS off-loading, increasing concurrent user support by 80%. This resulted in a 15% increase in new customer sign ups.● Deployment Efficiency:Accelerated deployment times by 30% and reduced operational costs by 200$ per month per server through containerization (Docker/Kubernetes) and automation (Ansible). Managed edge servers efficiently, enabling faster deployment cycles.● System Reliability and User GrowthAchieved 99.9% system uptime through infrastructure improvements and robust monitoring (influxdb, prometheus), enhancing user trust. Contributed to a 25% growth in active users and subscriptions by addressing bottlenecks and improving UX.● Development and Operational Efficiency: "Developed comprehensive user management and usage monitoring systems (Django rest framework, golang, rabbitmq, celery, grpc), resulting in a 20% reduction in operational tasks and improved resource allocation."

ForthGrid, a platform specializing in the manufacturing of mechanical parts, entrusted me with the role of Backend Developer.During my tenure, I was responsible for the following key outcomes:● Reduction in order management time due to the new CMS service:Revolutionized order management at ForthGrid by developing and implementing a comprehensive CMS service using Python and Django-rest-framework, which resulted in a 40% reduction in order management time. This transformation directly contributed to a 15% increase in order processing capacity.● Increase in part analysis accuracy and speed:Enhanced the precision and efficiency of part analysis by creating a service utilizing the Autodesk forge system, developed with fast-API and celery, leading to a 30% increase in analysis speed and a 25% improvement in accuracy. Overcoming the challenge of integrating complex geometrical data with manufacturing constraints in real-time, significantly boosting our capability to deliver customer parts.● Deployment success rate and uptime of the full cluster:ensured a 99.9% uptime for critical manufacturing operations by successfully deploying a full cluster using AWS EC2, RDS, ElastiCache, ELB, and SQS, thereby guaranteeing uninterrupted backend services.Navigating through complex AWS configurations and potential security vulnerabilities, my efforts were instrumental in achieving a 10% growth in production capacity.● Resource Optimization:Reduced operational costs by 20% through meticulous AWS resource optimization (Auto Scaling), promoting cost-effective scaling, ultimately leading to a more resilient and agile infrastructure capable of supporting a 25% increase in project deployments without additional costs.

"NeoLife" is a startup dedicated to leveraging state-of-the-art machine learning technology to support the In-Vitro Fertilization (IVF) process.As the Chief Technology Officer at NeoLife, I was responsible for spearheading the organization's technological endeavors. My key contributions included:● Performance Improvement of IVF prognosis models:Elevated IVF prediction model accuracy by 40% compared to classic methods through advanced machine learning modeling (TensorFlow, scikit-learn), leading to better patient management and 15% increase in successful patient outcomes.● Development and Deployment Efficiency:Accelerated product launch cycles by 50% through CI/CD implementation (GitLab, docker swarm), enabling rapid market response and a 20% increase in new feature releases.● Operational Efficiency Through MicroservicesModernized architecture with microservices (Docker, Kubernetes), achieving 30% greater scalability, 25% cost reduction, and laying the foundation for accelerated growth.● Impact on Frontend Development:Revitalized user experience with Vue/Nuxt, reducing load times by 50%, boosting engagement by 30%, and contributing to a 10% lift in user retention.

GenoDeep is a multidisciplinary organization specializing in artificial intelligence applications in the healthcare sector. During my tenure as the Chief Technology Officer, I led a team involved in various innovative projects, including:● Cancer Screening by Liquid Biopsy: ○ Developed a pioneering machine learning model to detect early-stage cancer from blood protein biomarkers, resulting in a potential 30% increase in early diagnosis and contributing to an estimated 10 years of quality-adjusted life year (QALY) gain per 100,000 individuals, based on cohort data simulations. ○ Collaborated with the renowned Golestan Cohort scientific team to refine and validate the liquid biopsy technique, enhancing the model's reliability for real-world scenarios. ○ Facilitated cross-disciplinary partnerships between computational scientists and clinical researchers, strengthening the scientific foundation of early cancer detection.● Mortality Risk Prediction for COVID-19 Patients: ○ Spearhead the design and deployment of a machine learning model that predicts COVID-19 patient mortality risk, securing a $500k grant for further development and implementation. ○ Forged a critical partnership with the Iran University of Medical Science, enabling the screening of 150,000 individuals and significantly aiding in the early identification of high-risk patients. ○ Alleviated hospital workload by implementing a predictive model for COVID-19 patient outcomes, resulting in an average 15% reduction in health staff workload and estimated saving of 1,500$ per patient in 6 targeted hospitals. out efforts resulted in cutting excessive admissions of 130 patients per 1,000.● Scientific Publications on MS, Autism, and COVID-19: ○ Contributed to the scientific community by authoring 5 peer-reviewed papers with over 100 citations on MS, Autism, and COVID-19, enhancing understanding in these vital research areas.

At "My Hotel," I contributed to the development of an internal management system and online booking service for hotels. My duties encompassed:● System Uptime and ReliabilityAchieved a remarkable 99.9% uptime for our online booking service, directly addressing the critical issue of booking interruptions that often led to guest dissatisfaction and potential overbookings. This was accomplished through the strategic implementation of horizontal scaling, load balancing, and cloud-based redundancy.● Operational EfficiencySpearheaded to optimize hotel operations, which tackled the significant pain point of delayed guest services, which was previously exacerbated by the manual processing of room status updates. By automating these updates and reporting mechanisms using Python, we effectively reduced the manual entry time by 4 hours per day. This substantial time saving translated into faster guest check-ins. Staff members could now allocate their time to more critical tasks, thereby elevating the overall guest experience by 10%.

"IrQuant" was an artificial intelligence investment adviser and portfolio manager. During my tenure, I spearheaded initiatives that demonstrably enhanced model performance, development efficiency, and financial impact, as detailed below:● Model Performance Improvement MetricsElevated model precision by 10% through meticulous feature engineering, incorporating advanced Machine learning (Tensorflow) techniques such as Layer Normalization and Dropout in convolutional neural networks (CNNs) and recurrent neural network (RNN) models, and implementing autoregressive integrated moving average (ARIMA). This refinement in predictive accuracy contributed to an enhanced trading strategy efficiency, translating into a 5% increase in annual profit by improving win-rates in trading algorithms.● Development Efficiency MetricsAccelerated Web-App responsiveness by 20% through strategic Django optimizations, including the implementation of Redis caching for session storage and real-time data, optimized RabbitMQ message queues for efficient background task processing, and query optimizations to reduce database load. These improvements led to a noticeably smoother user experience, fostering increased trading volume due to reduced latency and more reliable real-time data updates.● Financial Impact MetricsDeveloped cutting-edge abnormality detection by leveraging auto-encoder models, mitigating potential trading losses by $2M annually, safeguarding financial assets. The direct impact of this system was observed in the reduction of erroneous trades, ensuring a more secure and profitable trading environment.

Topsonic Co is a technical engineering company involved in state-of-the-art technological fields.During my tenure, I was responsible for the following key outcomes:● Improvement in Product Performance: ○ Enhanced 3-DOF nano-actuator precision matrices by 15% by integrating mechanical design with software development skills, through comprehensive redesign (autodesk inventor), FEA optimization (ANSYS), and PID controller development (MATLAB/Python). ○ Boosted laser controller response time by 20%, implementing closed-loop control algorithms (Python/C++). This improvement was further supported by optimizing the firmware for real-time response, showcasing the integration of software engineering prowess with understanding of hardware constraints to elevate product performance.● Reduction in Development Time: ○ Streamlined firmware development (C++) for Selective Laser Sintering (SLS) devices and 3D printers, slashing project timelines by 10% ○ Optimized design and coding processes for AVR and Arduino based embedded systems, cutting development time by 30%. This was facilitated through rigorous design-build-test cycles, demonstrating a proficient application of software engineering methods in the context of embedded systems, pivotal for mechanical device functionality● Cost Reduction in Manufacturing: ○ Implemented design for manufacturability (DFM) analysis in top-sonic 3D printers, carving out 30% in manufacturing cost reduction. ○ Slashed laser controller manufacturing cost through redesigned with off-the-shelf components, translating to $20,000 cost saving per unit. This achievement was made possible by blending mechanical engineering insight with cost-saving strategies through intelligent component selection and system design.

SabtOnline is a website designed to automate complex paper processes for the establishment and registration of official changes within a company. As a Software Developer, my key contributions and outcomes included:● Development and Launch of Web ApplicationSpearheaded the development of a Python Django web application, including drag-and-drop workflow for intuitive user experience and intelligent document validation. Introduced real-time status updates and visual process monitoring, elevating user engagement by 15%. These standout features underscore my commitment to delivering cutting-edge solutions that enhance user interaction and operational efficiency.● Automation of ProcessesAutomated official request for establishment of companies, translated in saving 20+ person.hours per week per request. This automation not only expedited the request turnaround times but also significantly alleviated the team's workload.● CI/CD Pipeline ConstructionAccelerated software delivery with CI/CD pipeline (GitLab and docker swarm), reducing code-to-production time by half and enabling faster feature releases. This strategic implementation fostered a more agile and responsive development environment.● Revolutionized code qualityEnhanced code quality and reduced post-deployment bugs by 20% through incorporating automated testing (unit and integral testing). This advancement directly translates to substantial cost savings estimated $50k per year and risk mitigation by preventing potential issues before deployment.