National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Technical Project Manager (Token Services SME)

Fractal
London
3 months ago
Applications closed

Related Jobs

View all jobs

AWS Architect

Senior Data Engineer (FTC)

Data Engineer

Data Entry And Quality Control (Admin and Clerical)

Senior Data Engineer, EMEA

Data Analyst - Local Authority

It has come to our notice that Fractal Analytics’ name and logo are being misused by certain unscrupulous persons masquerading as Fractal’s authorized representatives to approach job seekers to part with sensitive personal information and/or money in exchange of promise of lucrative job offers in Fractal. Please exercise caution and verify that the person approaching you is a genuine representative of Fractal Analytics, or an authorized consultant, before you provide any personal details or other non-public information. If in doubt, please write to to seek clarification or report any abuse.

Technical Project Manager (Token Services SME)

Location: London, UK

Notice Period: 60 days

Key Responsibilities:

  • Leverage Data to solve key business problems from the clients. They will be working on identifying or creating data driven solutions to solve key problems in the industry.
  • Prior experience in Financial Services or Payments industry is preferred (Visa, Mastercard, American Express, and Discover).
  • Collaborate with Visa’s business and data science teams to develop an understanding of needs.
  • Extraction of data from various data sources.
  • Data cleansing, transformation, and feature engineering.
  • Aggregation of historical data in desired reporting format and preparation of KPIs.
  • Preparation of data sets in various formats and provision of datasets to the client.
  • Automation of data extraction and delivery pipelines for ongoing data-feed engagements.
  • Development of proof-of-concept use cases, ad hoc analysis, and reporting.
  • Communication of findings and insights effectively to both technical and non-technical stakeholders through reports, presentations, and visualizations.
  • Clear understanding of tokenization in the payment’s world and other scheme related compliance requirements and opportunities.

Qualifications:

  • API functionality and integration.
  • Payment systems (e.g., VisaToken Services, Visa Account Updater).
  • Knowledge of RESTful APIs, JSON, or XML data formats.
  • Project manage the roll out of clients Implementation plan including detailed plan, weekly tracking and execution.
  • Strong mathematical and statistical skills.
  • Problem solving skills with a deep understanding of various algorithms in Data Science.
  • Ability to efficiently manipulate and analyze large datasets.
  • Excellent Communication and Problem-solving skills.
  • Deep knowledge of card acceptance ecosystem including acquiring and gateway.
  • Exposure and knowledge of the financial institutions sector.
  • Experience leading and managing complex projects with many stakeholders.
  • Strong Stakeholder management and communication skills.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

If you like wild growth and working with happy, enthusiastic over-achievers, youll enjoy your career with us!

J-18808-Ljbffr

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.