Data Science Manager

NielsenIQ
Oxford
3 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager – Property Tech – London

Data Science Manager - Property Tech - London

Data Science Manager – Property Tech – London

Manager, Data Science

Data Science and Analytics Manager

Data Analytics Manager

Overview

You will be responsible for leading and managing a dynamic team of data scientists. You will play a crucial role in overseeing the team's sprints, workload reviews, OKR and goal setting, and regular career planning. Working with peers within the CGA Technology group (GBS), you will align the Data Science initiatives with the company’s strategic direction and ensure delivery of our strategic goals.

Responsibilities
  • Lead, mentor, and manage a team of data scientists to ensure a high level of performance and productivity.
  • Foster a collaborative and innovative team culture that encourages continuous learning and professional development.
  • Coordinate and facilitate work planning sessions to define project scope, goals, and deliverables.
  • Manage the execution of sprints, ensuring that the team meets deadlines and delivers high-quality results.
  • Conduct regular reviews of team members' workloads using JIRA, providing guidance on prioritization and resource allocation.
  • Collaborate with team members to identify potential challenges and implement solutions to optimize workload distribution.
  • Work closely with the team to establish clear and measurable departmental goals aligned with the organizational objectives.
  • Monitor progress towards goals, identify obstacles, and implement strategies to ensure targets are consistently met.
  • Establish effective communication channels with cross-functional teams to understand project requirements and ensure alignment with organizational goals.
  • Foster a collaborative working environment by facilitating effective communication and knowledge sharing between data science and other teams within the GBS function.
  • Identify opportunities for process improvement within the data science team, optimizing workflows, and implementing best practices.
  • Stay abreast of industry trends and emerging technologies to enhance the team's capabilities.
Qualifications
  • 5+ years' experience of leading Data Science teams
  • Experience with cloud computing and storage (MS Azure preferred).
  • Experience with DataBricks (Development and Deployment)
  • Strong knowledge of optimization and / or machine learning algorithms
  • Strong knowledge of Python and the respective development tools (e.g. Jupyter, PyCharm)
  • Experience in SDLC and version control platforms
Benefits
  • Flexible working environment
  • Volunteer time off
  • LinkedIn Learning
  • Employee-Assistance-Program (EAP)
About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

Want to keep up with our latest updates?

Follow us on: LinkedIn | Instagram | Twitter | Facebook

Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit https://nielseniq.com/global/en/news-center/diversity-inclusion


#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.

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.