Data Scientist

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