Senior Data Analytics Manager (6 month Contract)

Samsung Electronics UK
London
6 days ago
Create job alert

Join to apply for the Senior Data Analytics Manager (6 month Contract) role at Samsung Electronics UK


Get AI-powered advice on this job and more exclusive features.


Position Summary

Since its founding in Suwon, Korea in 1969, Samsung Electronics has grown into a global information technology leader, managing more than 200 subsidiaries around the world. Samsung Europe is formed by 17 divisions (subsidiaries) that represent circa $32bn in sales. It has recently become the leading Consumer Electronics brand in the region in terms of recognition and most preferred by consumers.


The Data Analytics Manager role will work closely with Product Managers, tech ops and multi‑functional teams to manage, launch, and expand our services on TVs, mobiles and tablets. The role demands a mix of technical skills, business analysis and new product development management.


This role is a 6 month contract.


Role and Responsibilities
Your key responsibilities

  • Use multiple data sources to analyse, track, interpret and make clear and concise recommendations to the business on growth and revenue‑building strategies
  • Maintain and improve upon regular Key Performance Indicators reporting to key partners using a range of BI and presentation tools, including teams across commercial, marketing, editorial and HQ
  • Manage a range of analytics requests and be proactive in finding relevant insights to present to key partners
  • Identify and prototype new data processing projects to gain new insights into viewer behaviour: there is a constant need to refine our understanding of product usage
  • Setting up new processes and systems to make working with data more efficient
  • Researching new ways to make use of data to drive a change in Key Performance Indicators
  • The ability to collect, organise and interpret information to produce reports and communicating trends to non‑specialists to help make decisions
  • Develop our capacity to forecast performance and behaviour using AI and ML methods
  • Develop and manage positive working relationships with colleagues, content partners and other teams within Samsung and be able to give and take constructive feedback when needed

What We Need For This Role

To be successful, you will possess the following skills and attributes:



  • Proficiency in applying machine learning to real‑world problems
  • Previous experience working in a data and insights management role for consumer media or customer‑facing industry
  • Demonstrable experience deriving insights and value from data to improve important metric performance
  • Strong knowledge of SQL and working knowledge of ETL methods
  • Strong analytical skills with the ability to collect, organise, analyse, and disseminate significant amounts of information with attention to detail and accuracy
  • Advanced spreadsheet skills and good working knowledge of visualisation tools such as PowerBi, Domo, Quicksight or Tableau
  • Working knowledge (or an understanding of concepts) of GCP/AWS
  • A passion for learning the newest technologies and standards
  • Experience taking ideas from concept to finished product whilst retaining creativity and singularity of purpose
  • Effective planning and organisational skills. The ability to manage several initiatives at once and prioritising tasks effectively, and reacting to late requests and fast‑changing events
  • The ability to operate with autonomy and multi‑functionally in a collaborative way
  • Performance driven mentality – strong motivation to lead professionally and thrive in a fast‑paced and demanding environment
  • Ability to create and maintain comprehensive solution documentation

What Does Success Look Like?

An innovator, with fresh ideas and hands‑on approach are key. We want someone who is a positive and proactive team player, who would rather figure out a smarter way of doing something than keep doing it the same way. We are a diverse team with a start‑up mentality, knowing that we have the resources and potential of one of the most exciting tech companies that exists today.


Benefits

  • Hybrid working – 3 days in the office and 2 days at home per week
  • Car allowance
  • Pension contribution
  • Three volunteering days each year
  • Holiday – 25 days plus bank holidays and an additional day off for your birthday
  • Access to discounts on a wide range of Samsung products
  • Access to a discount shopping portal
  • Partner Colleagues are not eligible for Samsung Enhanced Paid Sick Leave but may be eligible for statutory payments from their payroll agency
  • Up to 20 (pro‑ra­ta) Partner Absence days per calendar year to be used in times of need

Equal Opportunities

We are an equal‑opportunity employer and value diversity at our Company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.



  • Please visit Samsung membership to see Privacy Policy, which defaults according to your location, at: https://account.samsung.com/membership/policy/privacy. You can change Country/Language at the bottom of the page. If you are European Economic Resident, please click here: https://europe-samsung.com/ghrp/PrivacyNoticeforEU.html


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data analytics Manager

Senior Data analytics Manager

Senior Data Analytics Manager, Runna

Senior Data Analytics Manager – Casino Insights

Senior Data Analytics Manager - Finance & Risk Insights

Lead Data Analyst

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 Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.