Legal & General is a UK financial services group and global investor. It manages assets, originates investments, and provides retirement and protection solutions, including pension risk transfer, life insurance, workplace pensions, and retirement income.
Задачи:
Partner with traders and global markets teams to understand data needs and deliver practical solutions.
Build and maintain scalable data pipelines, datasets, and analytical tools.
Support quantitative research initiatives, including developing and applying analytical models.
Identify gaps in data infrastructure and drive improvements to reliability and scalability.
Act as the first point of contact for data and analytics issues, diagnosing and resolving problems.
Collaborate with global stakeholders to support workflows across multiple regions.
Enhance data quality, governance, and accessibility across platforms.
Translate complex technical outputs into clear insights for non-technical audiences.
Требования:
Strong Python experience, including Pandas, NumPy, or similar data analysis libraries.
Advanced SQL skills and experience working with relational databases.
Experience building data pipelines, working with cloud platforms, and integrating APIs.
Solid understanding of data engineering principles and scalable data architecture.
Strong communication skills and ability to engage and collaborate with non-technical stakeholders.
Proven problem-solving ability and experience working in a fast-paced environment.
Будет плюсом: experience in financial services or a trading environment, data visualisation tools such as Tableau, exposure to advanced analytics or machine learning
Условия:
Annual performance-related bonus plan and share schemes.
Generous pension contribution.
Life assurance.
Healthcare Plan for permanent employees only.
At least 25 days’ holiday plus public holidays; 26 days after 2 years’ service; option to buy and sell holiday.
Competitive family leave.
Electric car scheme through tax-efficient salary sacrifice for permanent employees only.
Discounts on company products and at high street stores and online.
The role is 5 days per week on-site; hybrid working is not available for this role.
Flexible working options, including part-time, term-time, and job shares, may be discussed.
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