Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Analyst - TikTok LIVE - London

TikTok
City of London
2 weeks ago
Create job alert
Senior Data Analyst - TikTok LIVE - London

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


Responsibilities

  • The Regional LIVE Operation Strategy Team leads various cross‑functional projects. Our key initiatives include developing strategic plans to drive widespread adoption of LIVE at scale among creators, localizing new product features, creating user engagement strategies, ensuring a positive creator experience through education on the Community Guidelines and best practices, and providing ad hoc analysis and support to cross‑functional partners.
  • Uncover insights and deliver data‑driven recommendations that directly impact how we grow and support our creator ecosystem.
  • Work cross‑functionally with product, strategy, and operations teams to shape our growth priorities using data and analytical thinking.
  • Analyze local and global content and user trends to identify growth opportunities within the EU LIVE ecosystem.
  • Create, automate, and maintain reports and dashboards to track performance, OKRs, and key strategic initiatives.
  • Develop data models and perform in‑depth analyses to support content strategy, creator segmentation, and user engagement.
  • Translate complex data into actionable insights for regional teams and leadership.
  • Collaborate closely with cross‑functional teams (e.g., Creator Management, Product, Strategy) to inform decision‑making.
  • Present findings clearly to both technical and non‑technical stakeholders to influence business strategy.

Examples of Problems You’ll Be Solving

  • What are the best content verticals for us to focus our creator recruitment on?
  • How can we build a predictive model to identify high‑potential creators early?
  • What are the right leading and lagging indicators to measure success against our key OKRs?
  • How can we segment creators and users to better personalise support and growth strategies?
  • When and how should we educate creators to maximise their long‑term retention and performance?
  • How can we simplify complex data sets using statistical tools to better diagnose issues and recommend scalable solutions?

Qualifications
Minimum Qualifications

  • 5+ years of experience in data analysis, preferably in a high‑growth or tech environment.
  • Strong mathematical and analytical skills, with the ability to interpret large datasets and generate actionable insights.
  • Proficiency in SQL and at least one programming language (Python preferred).
  • Solid understanding of statistics and data modelling techniques.
  • Experience using data visualization tools such as Tableau, Power BI, or Looker.
  • High attention to detail and commitment to data accuracy.

Preferred Qualifications

  • Experience working in a consumer technology, content, or creator economy business.
  • Background in building predictive models or recommendation systems.
  • Familiarity with A/B testing and experimental design.
  • Strong communication skills, with the ability to simplify complex topics for non‑technical audiences.
  • Knowledge of the livestreaming industry or digital content ecosystems is a plus.

About TikTok

TikTok is the leading destination for short‑form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok’s global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.


Why Join Us

Inspiring creativity is at the core of TikTok’s mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy – a mission we work towards every day.


We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We’re resilient and embrace challenges as they come. By constantly iterating and fostering an “Always Day 1” mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.


Diversity & Inclusion

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst - SQL & Python

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior 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 Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.