Data Analyst

OSCAR ASSOCIATES (UK) LIMITED
Bromley
2 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Join to apply for the Data Analyst role at OSCAR ASSOCIATES (UK) LIMITED


£60,000-£75,000


The Role

We’re looking for a technically strong, commercially minded Data Analyst to join a fast‑growing consumer brand in the entertainment and iGaming space. This hands‑on role spans product, marketing, and commercial teams, with a focus on leveraging data to drive business growth and improve decision‑making.


BromleyHybrid (3 days per week)£60,000-£75,000


Successful Candidate

  • Analyse large‑scale datasets using SQL to uncover insights and inform strategy
  • Build and optimise dashboards in Looker Studio / BigQuery for multiple stakeholders
  • Support A/B testing, funnel analysis, and data modelling to enhance performance
  • Contribute to the evolution of the company's data warehouse and pipelines (experience with dbt or Airflow a plus)
  • Collaborate with product, marketing, and commercial teams to translate data into actionable recommendations
  • Communicate insights clearly across teams to influence business outcomes

Role Requirements

  • Strong technical skills in SQL and dashboarding tools (Looker Studio / BigQuery)
  • Experience with A/B testing, funnel analysis, and data modelling
  • Familiarity with data warehouse concepts and pipeline development (dbt, Airflow experience advantageous)
  • Ability to work collaboratively across multiple teams and communicate insights effectively
  • Proactive, detail‑oriented, and able to drive impact in a high‑growth environment

The Company

You’ll be joining a rapidly scaling consumer brand in the entertainment/iGaming sector. The business invests heavily in data and BI, fostering a collaborative and innovative environment where employees can influence commercial strategy, work with cross‑functional teams, and make a tangible impact on business outcomes.


Apply Now

If you are a talented Data Analyst looking to join a fast‑growing, high‑impact team, this could be the perfect next step in your career.


Oscar Associates (UK) Limited is acting as an Employment Agency in relation to this vacancy.


To understand more about what we do with your data please review our privacy policy in the privacy section of the Oscar website.


#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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.