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

Apply Now

Data Scientist

Hurelax Pte Ltd
City of London
1 week ago
Create job alert

Job Responsibilities:



  1. Participate in the design of A/B experiments and scientific evaluation mechanisms to guide product and strategy decisions in various business scenarios and enable rapid business iteration;
  2. Deeply involved in the underlying mechanism development of A/B testing systems, attribution systems, anomaly detection systems, etc., and provide professional data science support;
  3. Gain in-depth understanding of business needs and provide support and guidance for experiment analysis, anomaly attribution, and other data analysis tasks;
  4. Explore new experimental methods and analysis techniques using causal analysis, machine learning, and other technical means to continuously improve product capabilities.

Job Requirements:



  1. Bachelor's degree or above in statistics, applied mathematics, econometrics, operations research, computer science, or related STEM or business fields (preferred);
  2. Solid foundation in statistics, with a strong interest and research spirit in causal inference and experimental science;
  3. Familiar with Hive, Hadoop, big data computing frameworks, proficient in SQL and Python, with more than 2 years of experience in data analysis, data mining, or machine learning projects preferred;
  4. Good foundation in statistics, probability theory, and experimental design; strong data analysis and visualization skills; experience in A/B testing and attribution analysis is preferred.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.