Data Scientist - Financial Services

About the Role

Our client is looking for a talented and innovative Data Scientist to join their expanding financial services division in Birmingham . This role is crucial for leveraging complex datasets to extract actionable insights, build predictive models, and drive data-informed decision-making across the business. You will work with cutting-edge technologies and collaborate with cross-functional teams, including finance, risk, and product development, to uncover patterns and opportunities that enhance customer experience and optimize financial strategies. This is a unique chance to make a significant impact in a data-centric environment, fostering a culture of analytical excellence and innovation.

Key Responsibilities

• Develop and implement machine learning models for credit scoring, fraud detection, and customer churn prediction.
• Analyze large, complex datasets to identify trends, patterns, and anomalies relevant to financial markets.
• Design and execute A/B tests to evaluate the effectiveness of new strategies and product features.
• Collaborate with engineers to deploy models into production environments and monitor their performance.
• Communicate complex findings and recommendations clearly to both technical and non-technical stakeholders.

Requirements

• Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Proven experience (3+ years) as a Data Scientist , with a strong portfolio of successful projects.
• Proficiency in programming languages like Python or R, and experience with SQL.
• Deep understanding of statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP) is highly desirable.

Benefits

• Competitive salary and annual bonus structure.
• Fully remote working arrangement with flexible hours.
• Comprehensive private medical insurance and wellness programs.
• Generous annual leave allowance and professional development budget.
• Access to advanced training and development opportunities in data science.