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: https://www.straive.com/

Job Role: Lead, Data Science & Data Engineering

Function: Analytics & AI Consulting - Payments Domain

Employment Type: FTE

Location: San Francisco Bay Area, CA

The Engagement

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.

Role Summary

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.

Key Responsibilities

• Delivery leadership: Own scoping, planning, and execution of data science and data engineering workstreams; 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.

Required Qualifications

• 6-8 years of experience delivering data science projects for financial institutions (banking, payments, cards, lending, or similar regulated environments).
• Python - mandatory: Expert, production-level proficiency for data science and engineering (e.g., pandas, scikit-learn, and standard ML/data tooling).
• SQL - mandatory: Advanced proficiency working with large relational/analytical datasets, including performance-aware query design.
• Demonstrated ownership of end-to-end delivery - from problem framing through deployment - with measurable business outcomes.
• Experience leading or mentoring a team and managing delivery against client or stakeholder commitments.
• Strong communication skills; able to engage senior stakeholders and explain technical concepts clearly.
• Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field (or equivalent practical experience).
• Authorization to work in the United States and ability to work onsite in the San Francisco Bay Area.

Preferred Qualifications

• AWS (cloud) - preferred: Hands-on experience building and deploying data/ML workloads on AWS (e.g., S3, Glue, EMR, Redshift, SageMaker, or equivalent services).
• Direct experience in the payments ecosystem (issuers, acquirers, networks, or merchants) and familiarity with transaction-level data.
• Experience with modern data engineering practices: orchestration, data modelling, CI/CD, and large-scale distributed processing (e.g., Spark).
• Exposure to MLOps, feature stores, and model monitoring in production.
• Prior consulting or client-facing delivery experience.

This job description is not intended to cover or contain a comprehensive listing of all responsibilities, duties, or activities that are required. Responsibilities, duties, and/or activities may change, or new ones may be added at any time with or without notice.

If you are a motivated professional with a passion for delivering impactful solutions, we’d love to hear from you. Apply today to be part of a dynamic and forward-thinking team at Straive.

“Straive is an Equal Opportunity Employer. Our policy is clear: there shall be no discrimination based on age, disability, sex, race, religion or belief, gender reassignment, marriage/civil partnership, pregnancy/maternity, or sexual orientation.

We are an inclusive organization and actively promote equality of opportunity for all with the right mix of talent, skills and potential. We welcome all applications from a wide range of candidates. Selection for roles will be based on individual merit alone.”