Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

BA with (Data Analyst)

N Consulting Ltd
London
10 months ago
Applications closed

Related Jobs

View all jobs

NLP AI Agent Architect for QA Automation

Senior Data Engineer, Databricks, Home Based

Role : Business Analyst

Domain : Banking Domain experience

Location : London

Experience : 6-9 Years

 

 

Job Description

 

Banking experience required.

 

Accountabilities:

  • Investigate and analyse data issues related to quality, lineage, controls, and authoritative source identification.
  • Execute data cleansing and transformation tasks to prepare data for analysis.
  • Design and build data pipelines to automate data movement and processing.
  • Develop and apply advanced analytical techniques, including machine learning and AI, to solve complex business problems.
  • Document data quality findings and recommendations for improvement.

 

Expectations:

  • Advise key stakeholders, including functional leadership teams and senior management, on functional and cross-functional areas of impact and alignment.
  • Manage and mitigate risks through assessment, supporting the control and governance agenda.
  • Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
  • Demonstrate comprehensive understanding of the organization’s functions to contribute to achieving business goals.
  • Collaborate with other areas of work for business-aligned support areas to keep up to speed with business activity and strategies.
  • Create solutions based on sophisticated analytical thought, comparing, and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
  • Adopt and include the outcomes of extensive research in problem-solving processes.
  • Seek out, build, and maintain trusting relationships and partnerships with internal and external stakeholders to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.
  • Communicate insights and findings to stakeholders, ensuring that the information is understood and actionable

 

Additional Job Description: Join us as a Data Analyst at Barclays, where you will interpret data to provide insights that drive strategic decision-making across the business. You will collaborate with various teams to optimize processes, enhance data-driven strategies, and ensure compliance with industry regulations.

 

To be successful as a Data Analyst, you should have experience with:

  • Capturing business requirements and translating them into technical data requirements.
  • Logical data modelling (e.g., ERWIN, Archi, MagicDraw).
  • Analytical literacy within a complex end-to-end architecture and data analysis tooling (Python, R, SQL).
  • Background in the investment banking industry with good product knowledge in at least one asset class is desirable.
  • Knowledge of Wholesale Markets business and related data flows.
  • Sound grasp of the front-to-back process of an investment bank.
  • Strong analytical skills, able to demonstrate flexibility in problem-solving.
  • Enthusiastic and demonstrates a can-do attitude through appropriate behaviours.
  • Willingness and ability to share information, transfer knowledge, and expertise to team members.

 

 

Highly valued skills may include:

  • Experience in Business/Data analysis and storytelling methods to present complex data issues in a simple and engaging manner.
  • Passion for and commitment to ensuring data quality with meticulous attention to detail.
  • Experience in data and operating model process re-engineering and ownership.
  • Exposure to data integration design strategies for both internal and external customer usage.
  • Strong written and verbal communication skills, including documentation, and experience working with various stakeholders ranging from different business areas, technology, and project team members.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.