At a Glance
- Tasks: Transform raw data into insights that drive strategic decisions for major financial institutions.
- Company: Fast-growing international consultancy specialising in data, AI, and advanced analytics.
- Benefits: Competitive pay, flexible remote work options, and opportunities for professional growth.
- Other info: Hybrid work model with potential for exceptional candidates to negotiate flexibility.
- Why this job: Join a dynamic team and make a real impact on large-scale data science initiatives.
- Qualifications: Strong skills in data processing, Python, SQL, and stakeholder management.
The predicted salary is between 54000 - 66000 £ per year.
Location: hybrid 3 days per week onsite in either London or Sheffield (can be negotiated to 2 days per week for exceptional candidates in exceptional circumstances)
Remuneration: either £450/day INSIDE IR35, or £90-£100k permanent employed
Our client is a fast-growing international consultancy specialising in data, AI and advanced analytics for major financial institutions. With programmes running across the UK and Europe, they are expanding their team to support large-scale data science and modelling initiatives.
This is a Senior Data Scientist/Analyst role within their global banking client’s developer experience team, supporting a new organisation-wide analysis initiative. This role sits at the intersection of data engineering and analytics, and requires strong, critical data processing and presentation skills to translate raw, ambiguous data into insights that directly drive strategic decisions across the organisation.
- Stakeholder Management & Analysis: Drive organisation-wide analysis, autonomously conducting gap analyses and translating ambiguous business needs into clear technical roadmaps. Manage expectations directly with users and data owners, keeping delivery aligned to business priorities.
- Data Engineering: Architect, build, and scale robust data pipelines using Python and SQL across platforms such as BigQuery and PostgreSQL. Work within established team standards for data extraction, complex aggregation, and resilient exception management, contributing to their ongoing improvement.
- Statistical Analysis & Quality: Apply advanced, critical quantitative methods (Pandas, NumPy) to process raw data and derive actionable insights. Implement automated frameworks to ensure enterprise-grade data quality and continuous validation. Active use of modern LLMs (Claude, GitHub Copilot) to accelerate development and pioneer AI-assisted coding practices within the team.
Data Science Data Science Data Scientist (Remote) employer: Lithe Consulting
As a leading UK manufacturer in advanced polymer-based processes, this company stands out as an excellent employer by fostering a supportive and collaborative work culture where every employee's contribution is valued. With a commitment to innovation and long-term growth, employees benefit from ongoing development opportunities and a stable environment that prioritises their well-being and professional advancement.
