Data Analyst (SQL, PySpark, Python)

Halian
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Our client is seeking an experienced Data Analyst to support a key client engagement within their professional services division. This is an initial 1 year contract based in London, operating on a hybrid basis (2 days onsite per week) and falling inside IR35.

Key Responsibilities:

  • Independently manage data extraction, cleansing, and transformation activities
  • Develop production-grade analytics code using SQL, PySpark, and Python
  • Analyze large-scale datasets to generate actionable insights and visualizations
  • Collaborate across technical and business teams to drive data-driven decision making

Required Experience:

  • 3–5 years' hands-on experience in data analysis, insight generation, and data visualization
  • Proven expertise in SQL and PySpark, with solid working knowledge of Python
  • Background working with big data platforms, large datasets, and pipelines
  • Strong analytical thinking and a collaborative, self-directed working style
  • Experience in the Payments, FinTech, or financial services sector is highly desirable, though not mandatory

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeContract

Job function

  • Job functionConsulting
  • IndustriesIT Services and IT Consulting

Referrals increase your chances of interviewing at Halian by 2x

Sign in to set job alerts for “Data Analyst” roles.

City Of London, England, United Kingdom £39.00-£45.00 4 days ago

London, England, United Kingdom £70,000.00-£80,000.00 22 hours ago

London, England, United Kingdom 3 weeks ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 3 weeks ago

Data Analyst, EMEA Supply Chain Operations – 1 Year Fixed Contract

London, England, United Kingdom 6 days ago

London, England, United Kingdom 1 week ago

City Of London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 3 weeks ago

London, England, United Kingdom 3 weeks ago

London, England, United Kingdom 2 weeks ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

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.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.