Data Scientist – Fraud

Jobtailor; Leicester; On-site; GBP 60,000 - 90,000; Full time

Job summary

Jobtailor seeks a skilled ML professional to develop and deploy predictive models for claims, fraud and risk KPIs. You will work with ML engineers to bring models into production and monitor their business impact.

You will present findings to cross-functional stakeholders and explore new technologies to help set the team’s best practices. Strong commercial acumen and communication are essential.

Qualifications

• Proficiency in Python and ML libraries, with cloud deployment experience.
• Ability to link model performance to commercial KPIs.
• Experience using SQL for data extraction and modeling.
• Interest in emerging ML techniques and their business value.
• Ability to communicate across data science, data engineering, ML engineering, operations and commercial teams.

Responsibilities

• Develop best-in-class ML models to predict claims outcomes, fraud and risk KPIs.
• Collaborate with ML Engineers to deploy ML models into production.
• Monitor deployed models and tie performance to commercial KPIs.
• Present analyses and results to Operational and Commercial stakeholders.
• Explore new technologies and contribute to the team’s best practices.

Skills

Python Proficiency

Machine Learning Model Development

SQL Experience

Commercial KPI Linking

ML Model Deployment

Tools

ML Libraries

Cloud Environments

Job description

• Develop best in-class ML models to predict claims outcomes, fraud and other risk KPIs
• Work with ML Engineers to deploy ML models
• Monitor deployed ML models and link performance to commercial value KPIs
• Present your work to Operational and Commercial stakeholders
• Explore new technologies and contribute to setting team’s best practices.

Requirements

• Proficiency in Python and experience with ML libraries for building and deploying machine learning solutions in cloud environments
• Ability to think commercially and link ML model performance to commercial KPIs
• Experience using structured query languages (SQL)
• Keen interest in emerging new ML techniques and their commercial value
• Ability to communicate across teams of Data Scientists, Data Engineers, ML Engineers, Operational and Commercial stakeholders.

Core Competencies

Demonstrates expertise in developing and deploying machine learning models, with a strong focus on linking model performance to commercial KPIs. Proficient in Python and SQL, with a keen interest in emerging ML techniques and best practices.

Highest-signal resume keywords

• Python Proficiency
• Machine Learning Model Development
• SQL Experience
• Commercial KPI Linking
• ML Model Deployment

Hard Skills

• Machine Learning
• Model Monitoring
• Data Analysis
• Statistical Modeling
• Predictive Analytics

Soft Skills

• Communication
• Collaboration
• Commercial Thinking

Industry Keywords

• Claims Outcomes
• Fraud Detection
• Risk KPIs
• Best Practices

Tools & Technologies

• ML Libraries
• Cloud Environments