Data Scientist - Risk Analytics

About the Role

Our client, a forward-thinking financial services company based in Manchester , is seeking a highly skilled Data Scientist specializing in Risk Analytics . This fully remote role is crucial for developing and implementing advanced analytical models to identify, assess, and mitigate financial risks. You will leverage cutting-edge machine learning techniques and big data technologies to enhance risk management frameworks and drive strategic decision-making. This is an exceptional opportunity for a data-driven professional to make a significant impact in a rapidly evolving sector.

Key Responsibilities

• Develop, validate, and deploy machine learning models for credit risk, market risk, and operational risk.
• Utilize statistical and data mining techniques to analyze large datasets and extract actionable insights.
• Design and implement A/B tests and other experiments to evaluate model performance.
• Collaborate with risk management teams and business stakeholders to understand requirements and translate them into data science solutions.
• Build robust data pipelines and ensure the quality and integrity of data used for modeling.
• Stay abreast of the latest advancements in data science, machine learning, and risk analytics.

Requirements

• Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, or related discipline.
• Proven experience as a Data Scientist with a focus on financial risk.
• Strong programming skills in Python or R, and experience with SQL.
• Expertise in machine learning algorithms (e.g., regression, classification, clustering, deep learning).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical audiences.

Benefits

• Competitive salary and remote work flexibility.
• Comprehensive health, dental, and vision insurance plans.
• Generous pension contributions.
• Access to cutting-edge technology and learning resources.
• Supportive and innovative work environment.