Lead Data Scientist

Kantar Group
London
1 month ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist

Lead Data Scientist

Location: Reading, King’s Road


We’re the world’s leading data, insights, and consulting company; we shape the brands of tomorrow by better understanding people everywhere.


About the job

As a Lead Data Scientist, you will play a pivotal role in driving excellence for business optimisation! You will harness advanced analytical techniques and machine learning expertise to extract valuable insights from complex datasets. You will embed sophisticated data science techniques inside critical applications (such as pricing, yield etc).


The selected candidate will guide a team of data scientists in collaborating with cross-functional stakeholders, identifying business opportunities, recommending data-driven strategies, and shaping key decisions. You will deliver impactful solutions, optimising processes, and enhancing products. You will also promote a culture of continuous learning, empowering the team to push the boundaries of data science, catalysing growth and success for the organisation!


Job Goals

Collaborate with Data Engineering and other Data Science teams to launch and deliver key business optimisation projects within set timelines (examples include: Pricing, Yield, Forecasting Capacity, Media Optimisation etc)


Engage with diverse stakeholders across departments to understand business priorities and align data science initiatives accordingly.


Lead and mentor a team of data scientists to ensure successful completion of critical projects, meeting or exceeding expected outcomes.


Champion the adoption of new technologies, tools, and methodologies to enhance data processes and promote continuous improvement.


Establish and maintain robust visualisation and monitoring systems to track performance metrics and alert on key changes.


Promote best practices and compliance with Data Privacy and Data Security standards throughout all team activities.


Document all projects comprehensively, ensuring knowledge is shared and accessible for ongoing and future work.


Ideal Skills & Capabilities

Advanced Analytics Mastery: Expertise in data mining, predictive modelling, forecasting, optimisation and machine learning, delivering actionable insights and business optimisation solutions.


Technical Excellence: Deep proficiency in Python, possibly R for prototyping, SQL, and specialist tools such as Pandas, NumPy, Spark, and Dask; hands‑on experience with cloud platforms (Azure ML, AWS) and ML Ops for robust model deployment and automation. CI/CD pipelines experience is advantageous.


Ethical and Secure Data Stewardship: Extensive knowledge of data privacy, security compliance, and best practices for responsible data handling throughout the project lifecycle.


Leadership and Delivery: Demonstrated ability to lead and mentor high‑performing data science teams, managing complex projects from conception to impactful delivery in commercial environments.


Innovative Approach: Enthusiasm for exploring the latest technologies and integrating emerging best practices, ensuring continuous improvement and growth for both the team and the organisation.


What we Offer

As a Lead Data Scientist, you will have the opportunity to work with a diverse and dedicated team of data scientists, data engineers, and other professionals. You will be part of a team that shapes the future of panel market research and drives results for brands everywhere. You will also enjoy flexible working arrangements that support your health and wellbeing. You will have access to learning and development opportunities, mentoring and coaching, and career progression paths. You will also be part of a culture that values diversity, inclusion, and innovation, and encourages you to unleash your potential at Kantar.


Please be aware, the majority of our roles are hybrid, working three days a week in our office.


We’re not able to offer visa sponsorship or help with relocation support for this role. Please make sure you’ve got the right to work in the country where this role is located before applying.


What part of Kantar might I be joining?

You’ll be joining our Data division, home to specialists in survey design, sampling and data science. With the world’s largest audience network (over 170 million people), we’re trusted by many of the worlds leading brands to provide amazing insights from real people.


We shape the brands of tomorrow by better understanding people everywhere. By understanding people, we can understand what drives their decisions, actions, and aspirations on a global scale. And if we combine the expertise of our people with the latest AI technology, we can really help brands discover some amazing insights.


And because we know people, we like to make sure our own people are being looked after as well. Equality of opportunity for everyone is our highest priority and we support our colleagues to work in a way works for them. We encourage applications from all backgrounds and sections of society. Even if you feel like you’re not an exact match, we’d love to receive your application and talk to you about this job or others at Kantar.


Privacy and Legal Statement

At Kantar, the diversity of our employees provides a richer environment for our employees and broader depth and breadth of thinking for our clients. Kantar is committed to inclusion and diversity; therefore, we welcome applications from all sections of society and do not discriminate based on age, race, religion, gender, pregnancy, sexual orientation, gender identity, disability, marital status, or any other legally protected characteristics.


PRIVACY DISCLOSURE: Please note that by applying to this opportunity you consent to the personal data you provide to us to be processed and retained by The Kantar Group Limited (“Kantar”). Your details will be kept on our Internal ATS (Applicant Tracking System) for as long as is necessary for the purposes of recruitment, which may include your details being shared with the hiring manager.


#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.