Lead Business Analyst – Fraud

Neural Technologies
Liverpool
1 year ago
Applications closed

Related Jobs

View all jobs

Business Data Analyst

Data Analyst (Engineering)

Data Analyst Team Lead

Senior Data Analyst

Principal Data Analyst

Contract Principal Data Analyst - Hybrid - Reading

About Neural

Neural Technologies is a provider of modular revenue protection, machine learning/artificial intelligence, data integration and signaling software solutions for cross domain functions covering Telecom operators, Banking, Payment processors, and others.

Neural Technologies has a global presence with customers in 45 countries worldwide. The company has built an international reputation for providing quality solutions to increase the bottom line for its customers around the globe. Neural Technologies can reference Tier 1 & 2 converged service providers and network partners. We are a part of Lumine Group, a leading global acquirer of communications & media software businesses. Lumine Group is a division within Volaris Group, a subsidiary of Constellation Software Inc. (TSX:CSU), a multi-billion dollar global public company based in Canada and listed on the Toronto Stock Exchange.

 

Why Join Us

Neural Technologies offers exciting careers that provide the opportunity to work within an innovative and forward-thinking company. In line with our expansion and quest for quality excellence, we are seeking dynamic and career-minded individuals to join our team.


Business Analyst Skills and Knowledge:


Solution Design and Architecture:

  • Collaborate with business stakeholders to understand their business requirements.
  • Design comprehensive and complex solutions by leveraging our suite of products to address Telco RAFM needs, in an end-to-end perspective (from the data feed, mediation, anti-fraud configuration and data storage).
  • Create solution architectures and design frameworks that align with our services/products and industry best practices to meet customer requirements.
  • Ensure scalability, performance, security and integration capabilities are considered during solution design.
  • Work closely with internal and external project stakeholders to validate and refine solution designs.


Requirement Analysis and Business Analysis:

  • Conduct in-depth requirements gathering sessions with customers to understand their business needs.
  • Analyse and document business requirements, translating them into functional and technical specifications.
  • Ensure all risks, assumptions and dependencies, are correctly mapped and covered for the SoW and LoE.
  • Collaborate with business analysts and cross-functional teams to identify process inefficiencies and propose optimized solutions.
  • Perform gap analysis and feasibility studies to ensure the proposed solutions address the identified business needs.


Solution Implementation and Deployment:

  • Collaborate with development teams to ensure accurate and timely implementation of Telco RAFM solutions.
  • Provide technical guidance and support during solution implementation, including system integration testing (SIT) and user acceptance testing (UAT).
  • Participate in solution deployment activities, including planning, tuning, and monitoring for package releases.
  • Conduct solution configuration and customization based on customer requirements.


Fraud Detection & Prevention Systems Technical Skills and Knowledge:


Data Analytics:

  • Proficiency in data analysis tool, data mining and reporting tools like SQL, Python, R, for extracting, transforming, and analysing data.
  • Ability to work with large data sets to identify patterns, anomalies, and discrepancies.
  • Familiarity with data visualization tools (e.g., MS SRSS, Power BI, Tableau, QlikView) to create dashboards and reports for fraud detection system


Fraud Management System.

  • Understanding of how to configure, customize, and optimize fraud detection and prevention tools, including transaction monitoring, identity verification, and alert management.

Transaction Monitoring and Risk Assessment:

  • Ability to implement real-time transaction monitoring systems and evaluate risk levels based on various parameters such as user behaviour, transaction size, location, and frequency.

Fraud Case Management Systems:

  • Familiarity with fraud case management systems (e.g., Case Management Tools, or other fraud detection platforms), used for tracking, reporting, and managing fraud cases.
  • Ability to implement real-time transaction monitoring systems and evaluate risk levels based on various parameters such as user behaviour, transaction size, location, and frequency.


IT, Data Integration Technical Skills and Knowledge:


Understanding of Mediation Software:

  • In-depth knowledge of mediation platforms
  • Experience in configuring, customizing, and optimizing mediation systems for high-volume data processing, ensuring seamless data flow between different network elements and business systems (e.g., billing systems, CRM, OSS/BSS).
  • Language: object-oriented programming skills like C#
  • For backend: Linux shell scripting skills, Unix.
  • SQL/DML in Oracle database skills (Oracle, SQL, PostgreSQL)


Event and Data Mediation:

  • Knowledge of processing raw data, such as call data records (CDRs), service usage events, and other transactional data, and transforming them into standardized formats for downstream applications.
  • Experience in event correlation, data aggregation, and data filtering to prepare data for billing, reporting, and analysis.

Data Normalization & Transformation:

  • Strong skills in data normalization, standardization, and data transformation (e.g., converting data into formats like ASN1. XML, CSV, JSON, or flat files for integration with other systems).
  • Knowledge of ETL (Extract, Transform, Load) processes, tools, and techniques to move data between mediation systems and other business systems.


Qualifications & Requirements:

  • Bachelor's degree in a relevant field such as Telecommunications, Engineering, Computer Science, or Business Administration.
  • 10+ of years working experience with within the telecom industry
  • Proven experience as a Business Analyst, Solution Designer, Solution Architect, Technical Lead, Fraud Specialist, or correlated role.
  • Strong business analysis skills, including requirements gathering, process analysis, and documentation.
  • Proficiency in solution design and architecture, with a deep understanding of telecom systems and technologies.
  • Great communication and presentation skills across different levels and sorts of stakeholders (internal and external).
  • Excellent analytical and problem-solving abilities to identify customer’s needs, manage fraud risks, and propose effective solutions.
  • Consultancy and customer-oriented mindset.
  • Ability to work in a fast-paced and dynamic environment, managing multiple priorities and deadlines.
  • Knowledge of industry best practices and regulatory requirements related to Telcom RAFM.
  • Familiarity with our suite of products or similar telecom software solutions is advantageous.
  • Experience in the telecommunications industry, particularly in RA and Fraud Management Systems, is highly desirable.


Personal Skills:

  • Strong communication and interpersonal skills to collaborate effectively with cross-functional teams and stakeholders.
  • Possess drive, strong proactiveness and resolve to provide a high-quality service.
  • Act independently without the need for constant monitoring.
  • Facilitation skills, including scoping, requirements, and solution design workshops.


If you are ready to take the next step, kindly forward your resume to the recruiter at .


**Due to high number of applicants, only shortlisted candidates will be contacted.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.