Data Scientist

Edenbrook; Greater London; In loco; GBP 60.000 - 90.000; Tempo pieno

Descrizione del lavoro

Edenbrook is seeking a Data Scientist to join its established Data Science and Analytics team. You will develop and deliver data science solutions across the full ML lifecycle, from data prep and model development to deployment and monitoring.

You will collaborate with technical teams and commercial stakeholders, applying Python and ML techniques to solve business problems, automate processes and deliver actionable insights. Training and development are provided.

Competenze

• Proficient Python with clean, maintainable code.
• Strong ML knowledge and libraries (pandas, NumPy, scikit-learn, statsmodels).
• Solid statistical foundations: hypothesis testing, regression, uncertainty.
• Strong SQL skills for querying relational datasets.
• Experience in data cleaning, manipulation and preprocessing.
• Working knowledge of Git and version control.
• Strong analytical and problem-solving abilities.
• Excellent communication to explain technical concepts.
• Curiosity about business operations and how data science delivers value.
• Collaborative, eager to learn and open to feedback.

Mansioni

• Deliver data science projects covering data preparation, exploratory analysis, model development and validation.
• Contribute to the deployment and ongoing monitoring of machine learning models.
• Take increasing ownership of the full model lifecycle.
• Apply data science techniques to automate manual processes and improve business efficiency.
• Explore potential generative AI applications and use cases.
• Assess the quality and suitability of internal and external data sources.
• Produce analytical insights and reporting to support business decisions.
• Write clean, tested and maintainable Python code, following engineering standards and participating in code reviews.
• Contribute to cloud-based ML pipelines and develop knowledge of MLOps and CI/CD.
• Work with commercial, actuarial, IT and data engineering teams to understand requirements and identify opportunities for data science.
• Communicate findings, insights and limitations to technical and non-technical stakeholders.

Conoscenze

Python

ML techniques

SQL

Data cleaning

Git/version control

Analytical thinking

Communication

Strumenti

pandas

NumPy

scikit-learn

statsmodels

Git

Descrizione del lavoro

An opportunity for a Data Scientist to join an established Data Science and Analytics team within a specialist financial services business. The role will focus on developing and delivering data science solutions across the full machine learning lifecycle, from data preparation and model development through to deployment and monitoring. Working closely with technical teams and commercial stakeholders, the successful candidate will use data science to solve business problems, automate processes and generate actionable insights. The ideal candidate will have strong Python, machine learning and statistical foundations, alongside a genuine interest in developing their experience in production ML, cloud technologies and MLOps. Previous production experience is not essential, as training and development will be provided.

Key Responsibilities

• Deliver data science projects covering data preparation, exploratory analysis, model development and validation.
• Contribute to the deployment and ongoing monitoring of machine learning models.
• Take increasing ownership of the full model lifecycle.
• Apply data science techniques to automate manual processes and improve business efficiency.
• Explore potential generative AI applications and use cases.
• Assess the quality and suitability of internal and external data sources.
• Produce analytical insights and reporting to support business decisions.
• Write clean, tested and maintainable Python code, following engineering standards and participating in code reviews.
• Contribute to cloud-based ML pipelines and develop knowledge of MLOps and CI/CD.
• Work with commercial, actuarial, IT and data engineering teams to understand requirements and identify opportunities for data science.
• Communicate findings, insights and limitations to technical and non-technical stakeholders.

Must-Haves

• Strong Python programming skills, with the ability to write clean, structured and maintainable code.
• Good understanding of machine learning techniques and libraries such as pandas, NumPy, scikit-learn and statsmodels.
• Solid statistical foundations, including hypothesis testing, regression and quantifying uncertainty.
• Strong SQL skills, including querying and joining relational datasets.
• Experience in data cleaning, manipulation and preprocessing.
• Working knowledge of Git and version control.
• Good analytical and problem-solving skills, with an understanding of model validation and limitations.
• Strong communication skills and the ability to explain technical concepts to non-technical audiences.
• Curiosity about business operations and how data science can deliver commercial value.
• Collaborative approach, willingness to learn and openness to feedback.