Senior Data Scientist at Swedbank | Certified AI & Cloud Architect | AML | Risk | ML | GenAI | Prompt Engineer | Statistician | Duomenų mokslininkas
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From PhD in mathematics to new frontiers in artificial intelligence applications development. As a data scientist, architect, promt engineer and developer Algirdas is constantly on the odyssey of sharing the passion to explore the changing world of ideas in machine learning, AI, cloud, MLOps, AML, KYC, risk, ChatGPT, leadership and cognitive computing.
Vilniaus universitetas / Vilnius University
Doctor of Philosophy (Ph.D.), Applied Mathematics
January 1, 2004 – January 1, 2007
Vilniaus universitetas / Vilnius University
Master of Science (MSc), Applied Mathematics
January 1, 2002 – January 1, 2004
Vilniaus universitetas / Vilnius University
Bachelor of Science (BSc), Physics
January 1, 1998 – January 1, 2002
Swedbank
Senior Data Scientist in Anti-Financial Crime | AML Group Risk Control
July 1, 2019 – Present
Vilnius
IBM
AI & Cloud Architect
July 1, 2016 – July 1, 2019
Vilnius, Lithuania
ITSM COMPANY
Cloud Engineer
July 1, 2015 – July 1, 2016
Vilnius, Lithuania
DocLogix
Cloud Developer
April 1, 2015 – July 1, 2015
Vilnius, Lithuania
Vilniaus universitetas / Vilnius University
Research Scientist and Lecturer
September 1, 2007 – April 1, 2015
Vilnius, Lithuania
Vilniaus universitetas / Vilnius University
Data Manager
June 1, 2004 – September 1, 2007
Vilnius, Lithuania
Science and Encyclopaedia Publishing Centre
Content Manager
May 1, 2003 – August 1, 2004
Vilnius, Lithuania
G5) Creating a Culture of Change
June 24, 2026 – Present
C5) Building High-Performance Teams
June 24, 2026 – Present
T11) Edge Analytics: IoT and Data Science
June 24, 2026 – Present
T4) Devops For Data Scientists
June 24, 2026 – Present
P) General Data Protection Regulation (GDPR) Awareness Training
IBM
June 24, 2026 – Present
N) Cognitive Practitioner
IBM
June 24, 2026 – Present
E) Orchestrating Big Data with Azure Data Factory (Automation)
Microsoft
June 24, 2026 – Present
F) Scala Programming for Data Scientist
IBM
June 24, 2026 – Present
J) Processing Big Data with Hadoop in Azure HDInsight
Microsoft
June 24, 2026 – Present
T14) New Manager Foundations
June 24, 2026 – Present
U11) Azure DevOps
June 24, 2026 – Present
U10) Azure Enterprise Development: Governance and Infrastructure Deployments
June 24, 2026 – Present
U9) Azure Databricks Essential Training
June 24, 2026 – Present
J5) Developing Executive Presence (Vice President Series)
June 24, 2026 – Present
I5) Leading with Stories
June 24, 2026 – Present
F5) Inclusive Leadership (Head Director Series)
June 24, 2026 – Present
H5) Diversity and Inclusion in a Global Enterprise
June 24, 2026 – Present
T7) Kubernetes: Microservices
June 24, 2026 – Present
T7) Machine Learning & AI: Advanced Decision Trees
June 24, 2026 – Present
T6) Docker: Continuous Delivery
June 24, 2026 – Present
T5) Planning a Multicloud Solution
June 24, 2026 – Present
K5) Leading with Emotional Intelligence
June 24, 2026 – Present
T1) Designing for Neural Networks and Artificial Intelligence Interfaces
June 24, 2026 – Present
M) IBM Certified Designer - Cognos 10 BI Reports
IBM
June 24, 2026 – Present
D) Processing Real-Time Data Streams in Azure
Microsoft
June 24, 2026 – Present
B) IBM Certified Big Data Architect
IBM
June 24, 2026 – Present
C) Design and Implement Cloud Data Platform Solutions
Microsoft
June 24, 2026 – Present
L5) Modeling Courageous Leadership: Intelligent Disobedience
June 24, 2026 – Present
U7) Data Science on Google Cloud Platform: Designing Data Warehouses
June 24, 2026 – Present
U6) Creating a Culture of Learning (Manager Series)
June 24, 2026 – Present
U1) Tableau 10 Essential Training
June 24, 2026 – Present
D5) Leading without Formal Authority
June 24, 2026 – Present
T12) Deploying Scalable Machine Learning for Data Science (AIOps Series)
June 24, 2026 – Present
T9) Cloud Architecture: Advanced Concepts
June 24, 2026 – Present
G) Implementing Predictive Analytics with Spark in Azure HDInsight
Microsoft
June 24, 2026 – Present
L) IBM Certified Specialist - SPSS Modeler Professional v3
IBM
June 24, 2026 – Present
I) Deep Learning with TensorFlow
IBM
June 24, 2026 – Present
A) Architecting Microsoft Azure Solutions
Microsoft
June 24, 2026 – Present
M2) Project Management (Manager Series)
June 24, 2026 – Present
U12) Learning Neo4j
June 24, 2026 – Present
U8) Serverless Architecture (CloudOps Series)
June 24, 2026 – Present
E5) Developing Your Team Members
June 24, 2026 – Present
T8) Learning Data Science: Manage Your Team
June 24, 2026 – Present
T2) Building and Deploying Deep Learning Applications with TensorFlow
June 24, 2026 – Present
O) Cybersecurity and Privacy (Security)
IBM
June 24, 2026 – Present
H) Processing Big Data with Azure Data Lake Analytics
Microsoft
June 24, 2026 – Present
K) MCSA: Cloud Platform
Microsoft
June 24, 2026 – Present
U9) Azure Serverless Computing (NoOps Series)
June 24, 2026 – Present
U5) Enhancing Team Innovation
June 24, 2026 – Present
U4) Creating a High Performance Culture
June 24, 2026 – Present
U3) Executive Leadership (Director Series)
June 24, 2026 – Present
U2) Tableau 10 For Data Scientists
June 24, 2026 – Present
T17) Cloud Architecture: Design Decisions (Enterprise Architect Series)
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's experience is heavily skewed towards Data Science, AI, and Cloud Architecture, with a strong background in financial services and academic research. While the candidate has a diverse skill set, the target role of 'Frontend Developer' represents a significant departure from their recent career trajectory. There is a lack of recent, dedicated frontend development projects or roles. This indicates a potential mismatch with a team focused purely on frontend technologies and user interface development. The candidate's extensive experience in complex, data-intensive systems might bring a different perspective, but their direct cultural fit for a dedicated frontend role is questionable without further evidence of passion or recent work in this specific domain. Given the lack of specific frontend projects, the cultural fit score is low.
Soft Skills & Operational Fit
The candidate's resume highlights experience in engaging with diverse audiences, educating colleagues on AI adoption, and leading development teams. This suggests strong communication, leadership, and collaboration skills. The focus on MLOps and DevOps indicates an understanding of operational best practices for AI solutions. However, the target role is 'Frontend Developer', which is a significant mismatch with the candidate's extensive backend, data science, and AI architecture experience. While the candidate has some historical exposure to JavaScript, HTML5, and Angular, their recent and primary focus is not frontend development.