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Data Scientist - Job Opportunity at BNP Paribas

Hong Kong, HK
Full-time
Mid-level
Posted: June 3, 2025
On-site
HKD 600,000 - 900,000 per year (USD 77,000 - 115,000), reflecting Hong Kong's competitive financial services market and BNP Paribas' position as a leading European bank requiring specialized data science expertise in audit and compliance applications

Benefits

Access to comprehensive global banking expertise and cross-functional collaboration across CIB Global Banking, Securities Services, Markets Activities, and Investment Protection Services
Professional development through audit methodology training and exposure to diverse business requirements
Technical platform contribution opportunities enhancing career portfolio and technical leadership skills
Knowledge transfer programs facilitating skill development and networking across global hubs
Inclusive workplace culture with active employee networks including PRIDE for LGBTQIA+ community, MixCity for gender diversity, Ability network for disability support, and CulturAll for cultural diversity
Participation in cutting-edge AI and machine learning initiatives with direct access to IG Datalab Team collaboration
Carbon-neutral economy commitment demonstrating corporate social responsibility and sustainable finance expertise

Key Responsibilities

Drive strategic business transformation by translating complex business needs into innovative data science solutions that directly impact BNP Paribas' global operations across multiple business lines
Lead cross-functional partnerships with high-stakes business domains including CIB Global Banking and Securities Services to implement mission-critical data analytics use cases that influence major financial decisions
Architect and develop production-ready data-driven prototypes using cutting-edge technologies like Python and PowerBI, ensuring enterprise-level code quality and maintainability standards
Shape the technical infrastructure of the Data Analytics platform for IG Hub APAC, contributing to the technological backbone that supports regional operations
Execute strategic audit assignments using advanced Data Analytics techniques to identify critical outliers and anomalies that protect organizational integrity and compliance
Drive digital transformation initiatives by defining and showcasing innovative AI tool applications that revolutionize traditional audit and analysis workflows
Champion organizational change by promoting AI adoption across audit teams, directly influencing operational efficiency and analytical capabilities

Requirements

Education

Master's degree in business or information systems management, computer science, data science, data analytics or related field

Required Skills

Qualification in Artificial Intelligence, Big Data or Data Science Familiar with data visualization tools PowerBI, Tableau Knowledge in Finance Knowledge in Audit Python programming, R and other scripting knowledge JFrog Artifactory Bitbucket or other version control tool and containerization tools, such as Docker
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Sauge AI Market Intelligence

Industry Trends

The financial services industry is experiencing unprecedented digital transformation acceleration, with traditional banks investing heavily in AI and machine learning capabilities to maintain competitive advantage against fintech disruptors. This shift is creating substantial demand for data scientists who can bridge the gap between complex financial regulations and innovative analytical solutions. Regulatory technology (RegTech) is becoming increasingly critical in global banking, with institutions like BNP Paribas requiring sophisticated data analytics for compliance monitoring, risk assessment, and audit processes. This trend is driving demand for data scientists with dual expertise in finance and advanced analytics. Asia-Pacific financial markets are experiencing rapid digitization, with Hong Kong serving as a crucial hub for international banking operations. Financial institutions are establishing dedicated data science teams in the region to capture local market insights and support regional business growth.

Role Significance

Likely part of a 5-10 person data science team within the broader IG Hub APAC structure, with matrix reporting relationships across audit, technology, and business units. The role involves collaboration with global teams and knowledge sharing across multiple hubs.
Mid-level position with significant strategic impact, requiring independent project leadership and cross-functional collaboration skills. The role combines technical expertise with business acumen, positioning the incumbent as a key contributor to organizational digital transformation initiatives.

Key Projects

Implementation of machine learning models for fraud detection and anomaly identification in trading activities Development of predictive analytics solutions for credit risk assessment and portfolio optimization Creation of automated audit trail systems using natural language processing for regulatory compliance Design of real-time monitoring dashboards for operational risk management across multiple business lines

Success Factors

Strong technical proficiency in Python and machine learning frameworks combined with deep understanding of financial services regulations and audit methodologies Exceptional communication skills to effectively translate complex technical concepts into actionable business insights for senior stakeholders across diverse functional domains Adaptability and continuous learning mindset to stay current with rapidly evolving AI technologies and regulatory requirements in the dynamic financial services landscape Cross-cultural collaboration abilities essential for effective knowledge transfer and project coordination across BNP Paribas' global hub network

Market Demand

High demand driven by banking industry's digital transformation needs, regulatory compliance requirements, and the strategic importance of data-driven decision making in global financial institutions

Important Skills

Critical Skills

Python programming proficiency is absolutely essential as it serves as the primary development language for machine learning models, data analysis workflows, and integration with existing banking systems. The ability to write production-ready, well-documented code directly impacts the scalability and reliability of data science solutions. Financial domain knowledge is crucial for understanding the complex regulatory environment, risk management frameworks, and business processes that drive data science requirements in banking. This knowledge enables effective translation of business needs into technical solutions. Data visualization expertise using tools like PowerBI and Tableau is vital for communicating analytical insights to non-technical stakeholders and creating interactive dashboards that support business decision-making processes.

Beneficial Skills

Audit methodology understanding provides valuable context for developing analytics solutions that align with regulatory requirements and internal control frameworks, enhancing the practical applicability of data science work Containerization and version control skills using Docker and Bitbucket demonstrate software engineering best practices that are increasingly important for deploying data science solutions in enterprise environments Natural language processing capabilities offer significant value for analyzing unstructured financial documents, regulatory texts, and communication data, expanding the scope of analytical applications beyond traditional numerical data

Unique Aspects

Direct involvement in shaping AI adoption strategies across audit functions, providing exposure to cutting-edge applications of machine learning in financial compliance and risk management
Opportunity to work at the intersection of traditional banking expertise and innovative technology solutions, contributing to the digital transformation of one of Europe's most established financial institutions
Access to global knowledge networks and cross-hub collaboration opportunities, enabling professional development through international project exposure and best practice sharing
Contribution to sustainable finance initiatives aligned with BNP Paribas' commitment to carbon-neutral economy by 2050, combining data science expertise with environmental impact

Career Growth

Typical progression to senior roles within 3-5 years, with management opportunities emerging after 5-7 years of specialized experience in financial services data science

Potential Next Roles

Senior Data Scientist or Lead Data Scientist roles within BNP Paribas' global network Data Science Manager or Analytics Team Lead positions overseeing regional data initiatives Chief Data Officer or Head of Analytics roles in regional financial institutions Consulting positions specializing in financial services digital transformation

Company Overview

BNP Paribas

BNP Paribas stands as the leading European Union bank and one of the world's largest financial institutions, maintaining an uninterrupted presence in Asia-Pacific since 1860. The organization offers comprehensive financial services spanning corporate and institutional banking, wealth management, asset management, and insurance, positioning it as a dominant force in global finance.

As a systemically important global bank with significant market capitalization and regulatory influence, BNP Paribas maintains strong competitive positioning through its diversified business model and extensive international network, particularly in European and Asian markets.
Hong Kong serves as a strategic hub for BNP Paribas' Asia-Pacific operations, supporting the bank's significant corporate and institutional banking activities across the region. The location provides access to major Asian financial markets and serves as a gateway for European capital flows into Asia.
BNP Paribas demonstrates strong commitment to diversity and inclusion through structured employee networks and comprehensive support systems. The organization emphasizes collaborative innovation, professional development, and sustainable finance initiatives, creating an environment that values both individual growth and collective impact.
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