Mahsa Ebrahimian

I am a senior AI and financial crime leader with deep expertise in building and governing machine-learning systems for mission-critical environments. I currently lead AI-driven compliance and financial crime data science, where I oversee design, deployment, and governance of advanced fraud and AML models at scale. With a strong background in applied machine learning, anomaly detection, and graph analytics, I speciliaze in translating business expectations into practical, production-ready AI solutions. I enable organizations to evolve from legacy decision paradigms to explainable, scalable AI decision intelligence. Over the past several years, I’ve worked at the intersection of AI, fintech, and risk—designing fraud detection systems, leading cross-functional teams, and driving the shift toward data-driven, intelligent decisioning. My work focuses not only on model performance, but on real-world impact—balancing fraud prevention, customer experience, and regulatory requirements to protect global financial ecosystems. What sets me apart is my end-to-end ownership: from defining strategy and KPIs with business stakeholders, to building and deploying models, to navigating the complexities of compliance, operations, and production systems. I partner closely with business and technical leaders to translate strategic initiatives into actionable AI roadmaps, align cross-functional teams across engineering, MLOps, IT, and data governance, and ensure AI solutions move beyond experimentation into scalable, production-grade systems. My focus is on building AI that delivers measurable value—operationalized, reliable, and designed to scale. ** How I Can Help You: - I support professionals and teams looking to build impactful, real-world AI systems—especially in complex, regulated environments. I can help you: - Navigate AI adoption — move from ideas to practical implementation, aligning AI initiatives with business strategy and organizational readiness - Define and measure impact — design meaningful KPIs and connect ML outcomes to real business value, using metrics to guide roadmap and decision-making Productionize ML systems — take models from experimentation to reliable, scalable production with the right architecture, processes, and trade-offs - Drive cross-functional alignment — effectively collaborate with engineering, MLOps, data governance, and business stakeholders to deliver end-to-end solutions - Communicate and explain AI — translate complex models into clear, actionable insights for non-technical stakeholders, including risk and compliance teams - Apply AI in FinCrime contexts — design responsible and effective solutions for fraud detection, AML, and compliance use cases - Implement best practices — improve model monitoring, reduce false positives, and balance performance with customer experience and regulatory expectations

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  Artificial intelligence

  I build scalable, explainable AI for fintech and compliance, leading end-to-end ML from strategy to production with real business impact.

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  Data science

  With over 8 years of experience building machine learning models, I can : Advice on applying machine learning on business problems, help data scientists and startups create a clear roadmap for taking models into production, and coach them on explaining model decisions to non-technical stakeholders.

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  Leadership

  I lead cross-functional AI teams, align strategy with execution, and drive high-impact solutions while mentoring talent and influencing stakeholders.

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  Productized services

  Building AI solution or machine learning models for the purpose of productionalization, for scaleability and reuse.