Lead - Data Science & Data Engineering

Straive is a global leader in enterprise-grade data analytics and AI solutions, committed to empowering businesses across various industries with cutting-edge technology and expert insights. Backed by EQT, a top private equity firm, we are uniquely positioned to drive innovation through significant investments and an entrepreneurial spirit.

Our core focus is on delivering advanced Data Analytics & AI Solutions. By combining sophisticated technology with subject matter expertise, we deliver material impact on our clients' topline and streamline their operations. We specialize in providing tailored solutions across financial services, CPG, legal, pharma, life sciences, retail and logistics, helping them build robust data analytics and AI capabilities.

With a client base spanning 30 countries, Straive's strategically located teams operate from eight countries and is headquartered in Singapore. This global presence enables us to offer localized expertise with a worldwide perspective.

Join Straive to be part of a dynamic team at the forefront of data analytics and AI innovation. Here, you'll have the opportunity to contribute to transformative projects, supported by significant investments and an entrepreneurial drive fueled by our partnership with EQT.

Website:

Job Role:
Lead, Data Science & Data Engineering

Function:
Analytics & AI Consulting - Payments Domain

Employment Type: FTE

This role leads delivery on a long-running consulting program for a leading global payments network (a major financial institution operating at the centre of the card-payments ecosystem). The work spans data science and data engineering initiatives delivered for the client and its broader ecosystem of partners - including acquiring banks and merchants. Typical problems include building analytics and machine-learning solutions over large-scale transaction data, designing data pipelines and feature platforms, and translating commercial questions into measurable, production-grade data products.

Note:

Specific client details are confidential and will be shared with shortlisted candidates under NDA.

As Lead, you will own end-to-end delivery for a portfolio of data science and data engineering projects, managing a team of approximately five practitioners. You will be the senior technical and delivery point of contact for client stakeholders - setting solution direction, ensuring quality and timeliness, and growing the capability of your team. This is a hands-on leadership role: you are expected to remain close to the data and the code while steering strategy and people.

• Delivery leadership: Own scoping, planning, and execution of data science and data engineering work streams; ensure on-time, high-quality delivery against client commitments.
• Team management: Lead, mentor, and develop a team of ~5 data scientists and data engineers; allocate work, review output, and support career growth.
• Stakeholder partnership: Serve as the primary technical liaison to client and partner stakeholders (including acquirer- and merchant-facing teams); translate business goals into analytical solutions and communicate results to technical and non-technical audiences.
• Solution design: Architect end-to-end solutions - from data ingestion and pipelines to modelling, evaluation, and deployment - over large-scale, sensitive financial datasets.
• Hands-on contribution: Write and review production-grade Python and SQL; set engineering standards for reproducibility, testing, and code quality.
• Modelling & analytics: Guide the development of statistical and machine-learning models (e.g., segmentation, propensity, forecasting, anomaly/risk signals) tuned to payments and financial-services use cases.
• Governance & quality: Ensure compliance with data privacy, security, and governance requirements appropriate to regulated financial data.
• Practice growth: Contribute to estimation, staffing, and proposals; identify opportunities to expand the engagement’s scope and impact.

• 6-8 years of experience delivering data science projects for financial institutions (banking, payments, cards, lending, or similar…