Senior Data Analyst - RELOCATION TO ABU DHABI

SoftServe
Bristol
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst (12 Month Contract)

Senior Data Analyst - HOTH, Permanent

Senior Data Analyst

Please note: this position requires relocation to Abu Dhabi for a minimum period of 12 months. Project duration: 36 months+. Softserve will support relocation of selected candidates.


WE ARE

SoftServe is a global digital solutions company with headquarters in Austin, Texas, founded in 1993. Our associates are currently working on 2,000+ projects with clients across North America, EMEA, APAC, and LATAM. We are about people who create bold things, make a difference, have fun, and love their work.

Big Data & Analytics Center of Excellence, data consulting and data engineering branch at SoftServe. Starting as a group of three enthusiasts back in 2013, hundreds of Data Engineers and Architects nowadays build Data & Analytics end-to-end solutions from strategy through technical design and PoC to full-scale implementation. We have customers in Healthcare, Finance, Manufacturing, Retail, and Energy domains.

We hold top-level partnership statuses with all the major cloud providers and collaborate with many technology partners like AWS, GCP, Microsoft, Databricks, Snowflake, Confluent, and others.


IF YOU ARE

  • Experienced in data analysis within a healthcare environment for 3–5+ years
  • Skilled in working with large-scale healthcare datasets and generating actionable insights
  • Proficient in SQL and data visualization tools such as Power BI or Tableau
  • Familiar with healthcare metrics, KPIs, and statistical methods used in clinical or operational analysis
  • Detail-oriented with a strong focus on data accuracy, consistency, and compliance with healthcare standards


AND YOU WANT TO

  • Analyze healthcare data to support clinical and operational decision-making
  • Build clear, insightful dashboards and reports tailored to healthcare stakeholders
  • Collaborate with cross-functional teams on AI-driven or analytics-based healthcare initiatives
  • Contribute to improving data validation and standardization processes across healthcare systems


TOGETHER WE WILL

  • Address different business and technology challenges, engage in impactful projects, use top-notch technologies, and drive multiple initiatives as a part of the Center of Excellence
  • Support your technical and personal growth — we have a dedicated career plan for all roles in our company
  • Investigate new technologies, build internal prototypes, and share knowledge with the SoftServe Data Community
  • Upskill with full access to Udemy learning courses
  • Pass professional certifications, encouraged and covered by the company
  • Adopt best practices from experts while working in a team of top-notch engineers and architects
  • Collaborate with world-leading companies and attend professional events


All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability, sexual orientation, gender identity/expression, or protected veteran status. SoftServe is an Equal Opportunity Employer.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

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.

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.