Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

System Data Analytics Specialist (Fraud / Callsign Optimization)

Capitex
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Engineer

Senior Data Engineer

Data Architect

BI & Data Analyst - Power BI

Data Architect

Job Title: System Data Analytics Specialist (Fraud / Callsign Optimization)

Location: Remote (Global)
Contract Duration: 6 months (with possible extension)
Client: Leading Saudi Arabian Bank
Type: Contract / Consultant


About the Role

We are seeking a System Data Analytics Specialist with deep technical expertise in fraud analytics, digital identity systems, and Callsign platform optimization. The ideal candidate will have hands‑on experience configuring, tuning, and optimizing Callsign or similar fraud detection and authentication systems within a banking or financial services environment.


You will play a key role in enhancing the accuracy, performance, and effectiveness of fraud detection rules and behavioral analytics. Working closely with fraud strategy, risk, and technology teams, you’ll ensure the Callsign system is delivering maximum protection with minimal customer friction.


Key Responsibilities

  • System Optimization & Tuning

    • Calibrate and fine‑tune the Callsign fraud detection and authentication engine for optimal performance.
    • Analyze data models, risk signals, and rule outputs to identify false positives/negatives and optimize model thresholds.
    • Work on continuous improvement of Callsign workflows, journeys, and intervention logic.


  • Data Analysis & Insights

    • Conduct deep analytics on fraud event data, behavioral biometrics, and system logs.
    • Build dashboards, performance metrics, and reporting pipelines to monitor Callsign efficacy.
    • Collaborate with fraud analytics teams to detect trends and emerging threats.


  • Technical Implementation

    • Configure system integrations between Callsign and core banking systems, APIs, or orchestration layers.
    • Support the deployment of new fraud scenarios and machine learning models.
    • Manage test environments, perform regression testing, and validate production changes.


  • Stakeholder Collaboration

    • Liaise with fraud strategy, IT security, and vendor teams to drive performance improvements.
    • Document configurations, model changes, and system updates.
    • Provide expert guidance on Callsign data structures, risk scoring, and orchestration capabilities.



Required Skills & Experience

  • Mandatory

    • Proven experience working directly with Callsign (configuration, tuning, or analytics).
    • 5+ years of experience in fraud prevention, risk analytics, or authentication systems in the banking sector.
    • Strong SQL, Python, and data visualization skills (e.g., Power BI, Tableau).
    • Familiarity with behavioral biometrics, device fingerprinting, and event‑based fraud modeling.
    • Excellent analytical mindset and ability to interpret complex data flows.
    • Strong communication skills in English (Arabic is a plus).


  • Preferred

    • Experience with machine learning models used for fraud or risk scoring.
    • Exposure to other fraud platforms (e.g., ThreatMetrix, Feedzai, SAS Fraud Management).
    • Knowledge of regulatory environments in MENA banking and SAMA compliance standards.



What’s Offered

  • Fully remote engagement – work from anywhere.
  • 6‑month contract, with possibility of renewal.
  • Opportunity to work with a top‑tier Saudi financial institution on a strategic fraud prevention initiative.
  • Competitive daily rate, commensurate with experience.


#J-18808-Ljbffr

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.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.