Data Scientist

Aquent
Manchester
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist Placement

Job Title:Data Scientist (App & Gaming)

Client Location:Remote - must be UK based

Starting:ASAP

Salary/Pay Rate:up to £62.02 per hour

Hours:Full-time; 40-hour week

Duration:11 months


Location:Remote -must be UK based

Pay rate:up to £62.02 per hour - depends on location


We’re looking for aSenior Data Scientistto support the delivery of several key strategic projects.


App & Gamingis one of the largest advertising verticals at the client and is currently a key company priority. The team is responsible for:


  • Driving the performance of end-to-end ads delivery and ranking across the App & Gaming segment
  • Ensuring continued innovation by building new optimisation products and formats that best meet the evolving needs of our advertisers
  • Growing the reach and performance of Audience Network, the client’s solution for displaying ads in third-party apps and on third-party websites


Top 3 Non-Negotiable Skills:

  • Machine learning and technical systems expertise
  • Proficiency in SQL
  • Proficiency in Python or R


Key Responsibilities:

  • Conduct deep and thorough analysis to uncover patterns, insights, and opportunities to support the continued growth of the App & Gaming business
  • Generate and test hypotheses, and analyse and interpret the results of product experiments
  • Collaborate closely with engineers, product managers, and other cross-functional partners to translate insights into product direction
  • Provide business intelligence (BI) and data visualisation support to help leadership understand the health of the business
  • Apply knowledge of statistics, machine learning, programming, data modelling, and simulation to support the above initiatives


Required Skills:

  • Strong understanding of querying relational databases usingSQL, with experience working with very large datasets
  • 10+ years total industry experience
  • Proficiency in programming languages such asPythonand/orR
  • Excellent written communication skills, including the ability to convey complex information clearly and encourage in-depth discussion
  • Proven ability to drive alignment across a diverse set of stakeholders


Preferred Background:

  • Experience in advertising or ad tech
  • Background in the app or gaming industry


Day-to-Day Activities:

  • In-depth analysis of ad performance and delivery consistency
  • Investigating why different ads appear across apps in the Audience Network — assessing if it's desirable, understanding the causes, and identifying improvements
  • Diagnosing inconsistencies between components of the ad ranking delivery stack and proposing solutions
  • Designing and executing experiments to validate changes and drive performance improvements


Nice-to-Have Skills:

  • App industry experience
  • Strong experimentation background


*This role is open for a limited time. Next steps will be shared with shortlisted candidates ASAP. Due to the high volume of applicants, we may be unable to reply to each applicant individually. Thank you for taking the time to apply.


Client Description:

Our Client is the largest social media company in the world. They have substantial B2B and B2C advertising and media platforms, as well as a nonprofit initiative. With the mission of bringing people together, they now boast over 2 billion users, and are rapidly developing as they influence the world around us.


Aquent is dedicated to improving inclusivity & is proudly an equal opportunities employer. We encourage applications from under-represented groups & are committed to providing support to applicants with disabilities. We aim to provide reasonable accommodation for any part of the employment process, to those with a medical condition, disability or neurodivergence.

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

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.

Jobs

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.

Education

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.

🍪 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.