Senior Data Scientist.

Sotheby’s
London
7 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Social network you want to login/join with:

Established in 1744, Sotheby’s is the world’s premier destination for art and luxury. Sotheby’s promotes access to and ownership of exceptional art and luxury objects through auctions and buy-now channels including private sales, e-commerce and retail. Our trusted global marketplace is supported by an industry-leading technology platform and a network of specialists spanning 40 countries and 70 categories which include Contemporary Art, Modern and Impressionist Art, Old Masters, Chinese Works of Art, Jewelry, Watches, Wine and Spirits, and Design, as well as collectible cars and real estate. Sotheby’s believes in the transformative power of art and culture and is committed to making our industries more inclusive, sustainable and collaborative.

The Role:

We are seeking an experienced senior data scientist with a passion for extracting meaning from data and a relentless focus on execution. You will join our Data Science team within the larger Product & Technology division and will work closely with Product, Engineering, BI/Reporting, and Operations teams.

As a member of our small but mighty data science team, you will play an integral role in delivering high-impact data products and insights as well as influence the overall vision and strategy of data science within Sotheby’s.

Responsibilities:

  • Solve product or business problems using analytics, experimentation, and machine-learning
  • Research and devise innovative statistical models for data analysis
  • Implement models in production in collaboration with developers and data engineering
  • Own the process of gathering, extracting, compiling, and cleaning data as needed to execute and deliver on data products
  • Communicate and present findings and insights to relevant stakeholders and leadership
  • Keep current with technical and industry developments
  • Work effectively in a dynamic, delivery-oriented environment with concurrent projects

Ideal Experience & Competencies:

  • 3+ years of proven experience as a data scientist
  • Strong knowledge of statistics (e.g. hypothesis testing, statistical inference, regression), predictive modeling, machine-learning, data wrangling
  • Proficiency with at least one scripting language (ex. Python) and one data visualization tools (ex. Matplotlib, Tableau)
  • Excellent ability to communicate complicated and nuanced insights in an accessible language to relevant stakeholders
  • Problem-solving aptitude and business sense
  • Natural curiosity and creative mind

To view ourCandidate Privacy Noticefor the US, pleaseclick here.

To view ourCandidate Privacy Noticefor the UK, Hong Kong, France and Switzerland, pleaseclick here.


#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 to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

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

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.