Data Scientist

Jobtailor; Greater London; On-site; GBP 45,000 - 65,000; Full time

Job summary

Jobtailor in London seeks a data analyst/scientist to deliver fraud analytics and machine learning insights for client projects. You will work with large datasets to uncover fraud patterns, discuss findings with clients, and propose effective solutions while preparing reports and visualizations.

The role emphasizes Python, SQL, network analysis and cloud-based tooling, with opportunities to develop new model features and internal tooling.

Qualifications

• Experience or training as a data analyst, intelligence analyst or data scientist.
• Strong critical thinking skills and ability to diagnose data issues.
• Strong communication and presentation skills.
• Diligence, attention to detail, ability to prioritise and follow through on tasks.
• Experience with SQL and ability to run complex queries.
• Experience with Python for data analysis.
• Knowledge of supervised and unsupervised ML techniques.
• Knowledge, understanding or experience of network analysis (desirable).
• Hands-on experience with DBT (desirable).
• Must meet pre-employment checks, including right to work.

Responsibilities

• Work directly with clients to provide fraud analytics and ML model insights.
• Analyse datasets with millions of rows to identify fraud patterns, trends and emerging threats.
• Discuss fraud problems with clients and propose effective solutions.
• Prepare reports and present analysis findings to clients.
• Identify new model features and improve model performance.
• optimise graph network performance using network analysis.
• Gain hands-on experience with cloud infrastructure and tools to enhance client data and performance.
• Build internal Python tools to optimise and improve analytical capabilities.
• Discover fraud patterns and trends with data scientists and crime analysts.
• Develop useful narratives from exploratory data analysis and help clients understand their fraud activity.

Skills

Fraud analytics

Machine learning

Python

SQL querying

Network analysis

DBT

Data analysis

Tools

DBT

Cloud infrastructure

Graph network analysis

Job description

• Work directly with clients to provide fraud analytics and ML model insights
• Analyse datasets with millions of rows to identify fraud patterns, trends and emerging threats
• Discuss fraud problems with clients and propose effective solutions
• Prepare reports and present analysis findings to clients
• Identify new model features and improve model performance
• Optimise graph network performance using network analysis
• Gain hands‑on experience with cloud infrastructure and tools to enhance client data and performance
• Build internal Python tools to optimise and improve analytical capabilities
• Discover fraud patterns and trends with data scientists and crime analysts
• Develop useful narratives from exploratory data analysis and help clients understand their fraud activity

Requirements

• Experience or training as a data analyst, intelligence analyst or data scientist
• Strong critical thinking skills and ability to diagnose data issues
• Strong communication and presentation skills
• Diligence, attention to detail, ability to prioritise and follow through on tasks
• Experience with SQL and ability to run complex queries
• Experience with Python for data analysis
• Knowledge of supervised and unsupervised ML techniques
• Knowledge, understanding or experience of network analysis (desirable)
• Hands‑on experience with DBT (desirable)
• Must meet pre‑employment checks, including unspent criminal convictions, employment verification, and right to work

Core Competencies

Demonstrates expertise in fraud analytics and machine learning model insights, with strong capabilities in data analysis using Python and SQL. Proficient in identifying fraud patterns and trends, optimizing model performance, and effectively communicating findings to clients.

Highest-signal resume keywords

• Fraud Analytics
• Machine Learning Techniques
• Python for Data Analysis
• SQL Querying
• Network Analysis

Hard Skills

• Data Analysis
• Fraud Pattern Identification
• Model Performance Optimization
• Exploratory Data Analysis
• Complex Query Execution

Soft Skills

• Critical Thinking
• Communication Skills
• Attention to Detail
• Diligence
• Task Prioritization

Industry Keywords

• Data Analyst
• Intelligence Analyst
• Data Scientist
• Supervised Learning
• Unsupervised Learning

Tools & Technologies

• Cloud Infrastructure
• DBT
• Graph Network Analysis