Aleksandr Ahramovich
Head of AI/ML Center of Excellence
I lead companies through AI transformations by defining efficient applications of AI technologies and supervising the adoption journeys.
About Aleksandr
Aleksandr is an experienced AI leader with a proven track record of implementing successful AI/ML-driven solutions and managing large-scale projects from ideation to post-deployment support. With a strong background in artificial intelligence, Aleksandr has been directing the work of Itransition’s AI/ML Center of Excellence since 2019.
He is responsible for managing a unit of over 50 employees from cross-functional teams, providing guidance and mentorship to ensure their professional growth. He also guides companies through their AI transformations, giving advice on how to best introduce AI technologies into their existing tech ecosystems.
Examples of Aleksandr’s recent projects include the following:
- A financial system chatbot providing answers to users’ questions from the database
- A model predicting customer churn for an insurance company
- A computer vision solution for advertising efficiency analysis and reporting
- A stock price prediction model for a trading platform
- A plancton pathology recognition solution
Through his trusted leadership and dedication, Aleksandr is driving excellence in Itransition’s AI and ML technologies, such as computer vision, natural language processing, and data mining, helping multiple international clients achieve their goals and keep pace with the growing trend for applying AI-based technologies in various domains.
Expertise
- Artificial intelligence
- Machine learning
- Predictive analytics
- Computer vision
- Data science
- Neural networks
- Deep learning
- Data mining
- Speech recognition
- Reinforcement learning
- Fraud and anomaly detection solutions
- Recommendation systems
Education
Belarussian State University
BA, Business Administration and Management
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Published works
AI in social media: use cases, top tools & adoption challenges, February 13, 2024
Machine learning in marketing:
 10 use cases and implementation tips, September 19, 2023
Machine learning for fraud detection: essentials, use cases, and guidelines, September 26, 2023
Predictive analytics in finance: use cases, platforms & adoption guidelines, November 12, 2024
Artificial intelligence in HR: use cases, platforms & adoption challenges, December 20, 2023
Machine learning in real estate: use cases, examples, and adoption guidelines, August 31, 2023
AI in fintech: use cases,
 solutions & implementation challenges, December 20, 2023
Artificial intelligence in architecture: 10 use cases and top technologies, August 15, 2023
Computer vision in healthcare: applications, real-life use cases & adoption tips, April 30, 2024
Computer vision in manufacturing: 9 use cases, examples, and best practices, May 23, 2023
AI in the workplace: 10 key use cases, benefits, and challenges, September 12, 2023
Predictive analytics in retail: use cases, examples & adoption guide, August 22, 2023
AI in the automotive industry: use cases, success stories & adoption guidelines, October 10, 2024
Supervised vs unsupervised machine learning: a selection guide, October 31, 2023
Top machine learning use cases and industry applications, June 9, 2023
Machine learning in education: 10 use cases, examples, and benefits, June 23, 2023
Predictive analytics in healthcare: top use cases & adoption tips, March 5, 2024
Predictive analytics in HR: use cases and implementation advice, October 16, 2023
AI in CRM: top use cases, best platforms, and guidelines, June 29, 2023
AI in sports: top use cases, real-life examples & adoption challenges, November 15, 2023
Recommendation systems and machine learning: approaches and case studies, September 26, 2023