Technical Business Analyst

Synchro
Newcastle upon Tyne
1 year ago
Applications closed

Related Jobs

View all jobs

Tech Business Analyst: REST APIs & Data Modeling, Remote

Lead Data Architect & BA – FinTech MDM & AI

Lead Data Architect — Enterprise MDM & AI-Driven FinTech

Junior Data Analyst

Data Analyst (Migration) - FTC

Senior Business Analyst Data Analytics & AI Remote

Have You Thought of Relocating to Dubai?

Technical Business Analyst – Relocate to Dubai! – Full Relocation Package Available


Are you a skilled Technical Business Analyst with a strong foundation in data engineering, data modelling, and a passion for leveraging customer data to shape impactful business solutions? Are you ready to relocate to Dubai and contribute to innovative projects in the financial sector? This is your chance to join a forward-thinking organization in one of the world’s most dynamic cities, with a tax-free salary, full relocation package, and exceptional career advancement opportunities.


Why Relocate to Dubai?

  • Tax-Free Income: Maximize your financial rewards with tax-free earnings.
  • Full Relocation Support: Enjoy comprehensive relocation assistance, including flights, high-quality accommodation, and help with settling into Dubai’s vibrant lifestyle.
  • Career Growth: Dubai’s financial sector offers exposure to high-impact projects, professional development, and significant opportunities for advancement.


What We’re Looking For:

  • Experience: Technical Business Analyst or similar role, ideally with a focus on data-driven projects, data engineering, and data modelling.
  • Key Domain Knowledge: Proven experience working with customer data, incorporating insights from contact centres, customer service, or call centres into project development. Financial services experience is highly desirable.
  • Technical Skills:
  • Proficiency in data analysis, data modelling, and data visualisation tools.
  • Familiarity with data pipelines, ETL processes, and database technologies (SQL, NoSQL).
  • Understanding of data-driven decision-making and agile development practices.
  • Education: Bachelor’s degree in information systems, Business Administration, Data Science, or a related field. Advanced certifications in data engineering or analytics are a plus.


What You’ll Get:

  • A Competitive Tax-Free Salary
  • Comprehensive Relocation Package: Includes flights, accommodation, and medical insurance.
  • High-Impact Role: Collaborate with cross-functional teams to shape data-driven strategies and foster a culture of innovation in a leading financial organization.
  • Exceptional Lifestyle: Experience Dubai’s world-class infrastructure, cultural diversity, and outstanding quality of life.


Take the next step in your Technical Business Analyst career and make a difference in the financial sector. If you meet the requirements and are excited about this opportunity, please get in touch with Harry Egginton at Synchro Recruitment to discuss the role in detail.

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.

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

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

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

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.