Job Title: Data Scientist Location: London (Hybrid) Job Type: Contract Key Responsibilities: - Apply end-to-end data science lifecycle principles—including design, exploratory data analysis, model development, evaluation, deployment, monitoring, and maintenance—to new projects. - Contribute to the development, performance monitoring, and ongoing lifecycle management (retraining, optimization, and enhancement) of production data science models. - Design comprehensive data-driven solutions for complex business challenges using large and small datasets, including internal and third-party sources, and leveraging advanced machine learning or statistical techniques. - Collaborate closely with data scientists, data engineers, and cross-functional teams—including pricing and analytics—to support the advancement of analytics capabilities across the organization. - Write high-quality Python code following industry best practices for model development and deployment. - Continually expand domain expertise by researching emerging technologies and techniques and sharing knowledge within the team. Essential Qualifications: - Hands-on experience in data science or advanced analytics, or a strong passion and aptitude to grow in the field. - Ability to perform thorough research independently or within small teams, while meeting time-sensitive objectives. - Proficiency with version control systems and familiarity with IT delivery tools. - Strong understanding of how to apply machine learning techniques to solve practical business problems. - Experience in building predictive and prescriptive models and articulating insights clearly to target audiences. - Excellent written and verbal communication skills, including the ability to present findings effectively. - Eagerness to adopt best practices in software development. - Strong Python programming skills. - Experience with test-driven development using frameworks such as Pytest or equivalent. Desirable Skills: - Degree or postgraduate qualification (or equivalent experience) in a relevant field such as engineering, mathematics, physics, or statistics. - Domain experience in finance, insurance, or e-commerce is a plus but not required. - Experience deploying models in cloud environments. - Familiarity with machine learning frameworks and libraries such as TensorFlow, CatBoost, XGBoost, Scikit-learn, and Pandas. - Experience developing and integrating APIs. - Proficiency in SQL. - Background in software engineering and exposure to DevOps/MLOps practices. - Working knowledge of CI/CD pipelines. Regards Anita