National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Marketing Data Analyst

Harvey Nash
City of London
1 day ago
Create job alert

One of our big tech clients is hiring for a Marketing Science Partner.

Marketing Science Partner
Job Duration: 12 -Months
Location: UK Onsite - Hybrid- Brock Street(3 days per week in office)
Via PAYE

Skills:
Turkish Proficiency
Marketing Analytics
SQL
Marketing Mix Model(MMM)
Client Facing experience(Turkey)

The Marketing Science Partner is a highly quantitative measurement professional, with marketing analytics experience to drive the Facebook measurement strategy with our largest Global Advertisers. To successfully influence how client’s conduct and use measurement, the role will need to be able to work cross-functionally with advertisers, sales teams, and other members of the Marketing Science team.
The ideal candidate will be passionate about advertising, intellectually curious, and able to move fast while keeping focused on high impact projects. This role requires a strong understanding of the media landscape and ability to apply quantitative techniques to understand consumer behaviour and advertising effectiveness.

Marketing Science Partner Responsibilities:

  • Drive our global advertisers to measure true business value by operationalising analyses and research that will prove the value of Facebook’s advertising business.
  • Play a strategic role in developing the cross-platform and cross-media measurement approaches and learning agendas for our global clients
  • Conduct in-depth standard and custom ad effectiveness studies/meta-analysis for Facebook global advertisers to understand the relative impact of different marketing strategies across digital platforms and across media
  • Drive client, vertical, and industry adoption of learning & preferred measurement methodologies, products, and approaches
  • Engage in senior client conversations, presentations of results, and consult internally with the sales teams to advise them on marketing best practices using evidence based insights.
  • Provide feedback to and collaborate with Product, R&D, and Partnerships teams to identify opportunities for new features, products, and partnerships

    Requirements/Qualifications:
  • Experience in research, analytics, or ad effectiveness
  • A bachelor’s degree in psychology, statistics, economics, behavioural or social science or a related field
  • An understanding of online advertising and familiarity with branding and performance advertising and marketing frameworks, including ad effectiveness measurement techniques
  • Experience with statistical analysis, including but not limited to experimental design, modelling, or advertising research
  • Experience building connections with customers and team members through effective communication and collaborating cross-functionally
  • Comfortable communicating complex topics to a non-technical audience & experience of inspiring action based on data-driven insights including influencing advertiser planning and buying behaviour
  • A track record of operating independently, demonstrating creativity, being detail-oriented, and delivering results in a highly organised manner

Related Jobs

View all jobs

Marketing Data Analyst

Marketing Data Analyst

Marketing Data Analyst

Marketing Data Analyst

Data Science Manager

Data Analyst, AFRS

National AI Awards 2025

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.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.

Part-Time Study Routes That Lead to Data Science Jobs: Evening Courses, Bootcamps & Online Masters

Data science sits at the intersection of statistics, programming and domain expertise—unearthing insights that drive business decisions, product innovation and research breakthroughs. In the UK, organisations from fintech and healthcare to retail and public sector are investing heavily in data-driven strategies, fuelling unprecedented demand for data scientists, machine learning engineers and analytics consultants. According to recent projections, data science roles will grow by over 40% in the next five years, offering lucrative salaries and varied career paths. Yet many professionals hesitate to leave their current jobs or pause personal commitments for full-time study. The good news? A vibrant ecosystem of part-time learning routes—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn data science while working. This comprehensive guide explores every pathway: foundational CPD units and short courses, hands-on bootcamps, accredited online MScs, plus funding options, planning strategies and a real-world case study. Whether you’re an analyst looking to formalise your skills, a software developer pivoting into data or a manager seeking to harness data-driven decision-making, you’ll find the right route to fit your schedule, budget and career goals.

The Ultimate Assessment-Centre Survival Guide for Data Science Jobs in the UK

Assessment centres for data science positions in the UK are designed to replicate the multifaceted challenges of real-world analytics teams. Employers combine psychometric assessments, coding tests, statistical reasoning exercises, group case studies and behavioural interviews to see how you interpret data, build models, communicate insights and collaborate under pressure. Whether you’re specialising in predictive modelling, NLP or computer vision, this guide provides a step-by-step roadmap to excel at every stage and secure your next data science role.