Reporting directly to the Managing Partner, the AI Data Scientist – Deal Origination Systems is the firm’s sole in-house technical specialist, responsible for the design, operation and continued development of Meridian, Armor Capital’s proprietary AI-driven deal origination platform, together with the quantitative screening models and data infrastructure that support the M&A practice.

The role sits at the intersection of three disciplines that are rarely combined in a single practitioner: applied machine learning and large language model engineering; production data engineering; and substantive corporate finance and M&A domain knowledge. The holder translates the Partners’ commercial hypotheses into deployed analytical systems, and is accountable for the accuracy, defensibility and confidentiality of the outputs those systems produce.

This is a standalone specialist position. The holder works directly with the Managing Partner and the deal team, without a supervising technical manager, and is expected to exercise independent professional judgement on architecture, model design and data governance.

Position particulars

• Department: Mergers & Acquisitions / Technology
• Reports to: Managing Partner
• Employment type: Full-time, permanent (continuous contract)
• Location: United Centre, 5/F, 95 Queensway, Admiralty, Hong Kong
• Remuneration: HK$25,000 per month plus discretionary bonus, MPF and medical benefits
• Working hours: 40 hours per week, Monday to Friday

Ownership of the Meridian origination platform

• Hold end-to-end technical ownership of Meridian, the firm’s proprietary AI-driven deal origination service, spanning the data model, entity resolution logic, lead scoring and tiering framework, personalization engine and campaign analytics
• Maintain and extend the underlying full-stack M&A referral and deal-flow platform, including its authentication layer and automated pipelines for real-time deal broadcasting
• Define the technical roadmap for the platform and prioritise development against the deal team’s commercial requirements

Quantitative screening and fit-scoring models

• Design, calibrate and operate proprietary screening and fit-scoring models that rank private-company universes against defined acquirer mandates and investment criteria
• Ingest and reconcile financial, ownership, sector and market data to produce tiered, evidence-backed acquirer and target shortlists at mandate scale
• Validate model outputs against transaction outcomes and refine scoring methodology accordingly

Applied AI and large language model engineering

• Build and maintain production tooling on large language model APIs, including reusable agentic components and automated build pipelines for target scoring, company research, entity classification and structured document generation
• Establish and operate systematic output-evaluation frameworks that hold machine-generated analysis to advisory-grade accuracy before it reaches a client or a Partner
• Maintain written model documentation sufficient for a third party to review the basis of any output relied upon in a client deliverable

Data architecture and governance

• Own the firm’s CRM data layer as the single source of truth for the deal pipeline, including ingestion, encoding remediation, de-duplication, entity resolution and taxonomy design
• Design and operate ETL pipelines and data acquisition tooling drawing on private-company databases, professional networks, corporate registries and public APIs
• Ensure all data handling complies with the Personal Data (Privacy) Ordinance (Cap. 486), the firm’s AML/CFT and client confidentiality obligations as a licensed TCSP, and applicable third-party data licence terms

Advisory support and technology assessment

• Translate the Partners’ commercial and financial hypotheses into precise technical requirements, and hand over documented, maintainable tooling to non-technical colleagues
• Conduct structured build-versus-buy assessments of emerging AI and corporate finance data tools, and make reasoned recommendations on integration into the firm’s technology stack
• Support live mandates with bespoke analysis, buyer-universe construction, comparables benchmarking and target screening as required

Essential qualifications and experience

Candidates must satisfy all of the following:

• Education. A master’s degree in data science, business analytics, statistics, computer science, artificial intelligence, applied mathematics or a closely related quantitative discipline, from a recognised institution. A bachelor’s degree alone is not sufficient for this position
• Professional experience. A minimum of twelve (12) months’ post-master’s professional experience applying data science and large language model engineering within a corporate finance, M&A, private equity, investment banking or comparable professional services environment. Experience gained solely in an academic or research setting does not satisfy this requirement
• Production ownership. Demonstrable end-to-end ownership of at least one deployed data or AI platform in a commercial setting, from data model through to live user-facing output. Candidates must be able to evidence work in production, not prototypes
• Technical stack. Advanced Python (Pandas, NumPy, scikit-learn) and SQL; ETL pipeline design, web data acquisition, entity resolution and de-duplication at scale; supervised and unsupervised learning, time-series forecasting, feature engineering and validation workflows; version control and reproducible workflows
• LLM engineering. Practical experience integrating large language model APIs into production systems, including prompt engineering, agentic tool design and systematic evaluation of generated output
• Corporate finance domain knowledge. Working command of company valuation, comparables and transaction benchmarking, buyer-universe construction, target screening criteria and deal origination practice, sufficient to work directly with Partners without technical translation
• Full-stack capability. Sufficient front-end and back-end capability to ship and maintain internal applications independently, including a modern JavaScript framework and a relational database platform
• Language. Professional working English, and fluency in at least one additional European language relevant to the firm’s European origination coverage. The role requires direct engagement with European counterparties, corporate registries and source documentation in the original language

Desirable

• Hands-on experience with Odoo or a comparable enterprise CRM as a structured data platform
• Prior migration or remediation of a corporate contact or pipeline database in excess of 10,000 records
• Familiarity with workflow automation and low-code data tooling
• A third European language

Core competencies

• Independent professional judgement; able to operate as the sole technical specialist without supervision
• Precision and intellectual honesty in handling analysis that will be relied upon in client-facing advice
• Commercial acumen and the ability to communicate technical constraints to a non-technical audience
• Discretion in handling confidential client, counterparty and transaction information

Compensation & Benefits

• HK$25,000 per month plus discretionary bonus, commensurate with experience
• Employee pension (MPF)
• Medical and dental insurance
• Additional leave and paid sick time
• Work from home arrangements
• Opportunities for promotion

Armor Capital |Investment & Advisory

Armor Cane Limited, trading as Armor Capital, is a Hong Kong-based corporate finance and advisory firm. The firm advises on cross-border mergers and acquisitions, corporate structuring and transaction execution, with a client and counterparty base spanning Asia and Europe. The firm operates a proprietary technology stack that underpins its origination and screening capability. This role holds technical ownership of that stack.

Our Services:

• M&A advisory (Buy & Sell side)
• Capital raising & financing (Debt & Equity)
• Divestitures & restructuring
• Strategic consulting

Visit our website: www.armor-capital.com