Top Machine Learning Jobs in Kuala Lumpur

Analyze complex datasets, develop and optimize statistical and machine learning models, and create AI solutions for business challenges. Clean and validate data, evaluate model performance, and collaborate with engineering, IT, and business stakeholders on deployment and improvement. Communicate analytical findings through reports, visualizations, and presentations while translating technical results into actionable recommendations. The role also requires staying current with data science, machine learning, generative AI, and responsible data practices.

Develop machine learning and advanced analytics solutions for risk management, including predictive models, GenAI, agentic AI, data pipelines, dashboards, and automated reporting. Analyze complex datasets to identify emerging risks, control weaknesses, and non-compliance. Collaborate with stakeholders to deliver scalable analytical solutions, support model deployment and monitoring, and communicate insights to technical and executive audiences.

Lead the global strategy and roadmap for recommendations and personalization across three ecommerce platforms. Partner with data science, analytics, engineering, and regional teams to translate customer intent and machine-learning capabilities into scalable discovery experiences. Own experimentation, relevance, engagement, conversion, and commercial outcomes while balancing shared capabilities with local market needs.

Lead risk-based internal audit planning and end-to-end engagements for a global cryptocurrency exchange. Evaluate governance, risk, and controls; produce audit reports for management and the Board; monitor remediation; and use SQL, AI, and advanced analytics to improve audit testing and risk assessment. Collaborate with Compliance, Risk, and Finance teams while addressing cross-border regulatory requirements and emerging risks in cryptocurrency, DeFi, and blockchain.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Drive new-logo acquisition and expansion across Napier AI’s Asia-Pacific client base. Build territory plans, develop senior relationships within financial institutions and regulated organizations, manage complex enterprise sales cycles, deliver proposals and business cases, navigate procurement and legal processes, negotiate commercial terms, and partner with internal teams on upsell, cross-sell, renewals, and customer growth.

Develop and deploy predictive, prescriptive, and machine learning models for supply chain challenges such as demand forecasting and inventory optimization. Build Python, SQL, and data models, apply advanced statistical techniques, validate data quality, and identify trends and anomalies. Partner with supply chain teams to translate business needs into analytics solutions, present insights, and continuously improve deployed models.

Leads end-to-end Record-to-Report process architecture across 16 European and APAC markets. Owns standardization, IFRS-compliant continuous close, SAP S/4HANA optimization, automation, AI adoption, internal controls, and SSC governance. Manages and develops the regional R2R team while partnering with IT, accounting, tax, audit, and finance leadership to deliver large-scale transformation and improved reporting accuracy.

Leads enterprise AI transformation across banking business units, identifying use cases, developing strategies, and overseeing AI projects from proof of concept through deployment and monitoring. Collaborates with business, data science, engineering, and IT teams; evaluates technologies and vendors; establishes responsible AI governance; mentors specialists; and presents business cases and recommendations to senior management.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Leads group-wide non-financial and operational risk management across methodology, risk appetite, controls, RCSAs, incidents, governance reporting, and risk training. Oversees operational risk data quality, provides independent challenge, investigates root causes, tracks remediation, and supports strategic risk transformation projects. Requires strong financial services knowledge, stakeholder influence, data analytics, AI, machine learning, automation, communication, and change leadership capabilities.

Leads complex data mining and machine learning initiatives, develops data-driven insights and business solutions, tracks analytics revenue, and aligns stakeholders on deliverables and standards. Provides thought leadership on emerging data science trends, mentors data scientists and team members, supports analytics projects, and contributes to data science strategy and best practices.

Develops data-driven insights and machine learning models to support business decisions and revenue or cost goals. Provides analytics reporting, collaborates with business stakeholders to align solutions and standards, contributes to data science strategy, and mentors team members on analytics projects.

Develops end-to-end fund security and anti-fraud risk strategies across financial products. Analyzes transaction data with Hive SQL and Python, reconstructs attack chains, quantifies losses, evaluates experiments, and deploys real-time rules. Responds to major security incidents, builds risk intelligence libraries, monitors metrics, and improves decision systems through collaboration with algorithm, product, engineering, compliance, and operations teams.

Leads internal audit analytics, automation, fraud surveillance, continuous monitoring, and AI-driven risk detection. Builds SQL models, audit-ready datasets, dashboards, alerts, and automated procedures using data from warehouses, internal systems, and blockchain sources. Partners with audit, IT, and data engineering teams to translate operational risks into analytical solutions, support investigations, quantify findings, and improve audit planning, testing, reporting, and control assessment.

Perform legal data collection, evaluation, and annotation for AI-powered contract management platforms in Simplified Chinese. Analyze clauses, obligations, and terms in international business contracts; participate in onboarding, calibration, and quality reviews; and collaborate within secure client environments. Requires contract or legal expertise, strong legal interpretation and contract-review skills, and fluency in English and Simplified Chinese. Prior data annotation or machine learning evaluation experience is preferred.

Lead research on improving AI agent training data and evaluations. Manage and mentor research engineers, define research direction, design rigorous experiments, validate data quality, diagnose reward and grading failures, and translate findings into scalable tools, workflows, and standards. Collaborate with engineers, domain experts, and vendors while communicating technical conclusions and tradeoffs clearly.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Leads global supply chain optimization by designing scalable processes, standards, training, metrics, and technology capabilities. Oversees procurement and ERP roadmaps, Oracle Fusion governance, AI and analytics adoption, MRP policies, standard costs, supplier performance, and continuous improvement. Drives transformation initiatives, change management, shared services, executive reporting, and M&A integration across divisions and geographies.

Lead pre-sales, consultative selling, and solution architecture for Experian’s Ascend Platform in Malaysia. Develop tailored SaaS solutions for banks and lenders, manage complex enterprise opportunities, conduct executive workshops, create business cases and technical proposals, and demonstrate capabilities across data, analytics, credit risk modeling, ModelOps, GenAI, and decisioning. Strengthen pre-sales frameworks, support go-to-market execution, assess business processes, and translate regulatory and market needs into product and roadmap insights.

Leads regional fulfillment analytics and performance operations across Malaysia, the Philippines, and Indonesia. Responsibilities include defining KPIs, resolving data-quality issues, managing stakeholder data requests, conducting UAT, building automated Looker dashboards, supporting process improvements, documenting workflows, and coaching team members. The role requires strong SQL, Looker, Excel, and data-analysis skills, with supply chain or warehouse operations knowledge and optional Python, R, predictive analytics, and machine learning experience.

Build privacy and anonymization systems that detect and transform PII, credentials, secrets, and other sensitive information in data used for AI training. Develop detection methods combining rules, statistical models, classifiers, and LLMs; create production data-processing pipelines; evaluate privacy risk and retained utility; and ensure robustness against schema drift, unusual formats, leakage, and adversarial re-identification.

Own digital product delivery from strategy and requirements through execution and optimization. Responsibilities include prioritizing features, managing roadmaps and backlogs, collaborating with engineering, design, marketing, and stakeholders, analyzing markets and customer feedback, facilitating requirements workshops, and monitoring product metrics. The role focuses on scalable technology products, with preferred experience in fintech, payments, banking, loyalty, e-commerce, or AI-powered platforms.

Own product initiative delivery from kickoff through release, coordinating Product, Engineering, Data, and Solutions. Track dependencies, risks, blockers, scope changes, timelines, testing, handoffs, and launch readiness. Maintain accurate project status and documentation while ensuring execution remains aligned with product intent. This hands-on role requires technical fluency, cross-functional communication, strong ownership, and daily overlap with an Asia-based technology team.

Analyze and interpret complex data using machine learning, artificial intelligence, and advanced analytics. Transform findings into actionable insights that support organizational decision-making, business strategy, and improved outcomes. Clearly communicate technical concepts and data insights to both technical and non-technical audiences.