Senior Data Scientist
HaystackAbout the role
We're working with a leading digital media company that publishes content across various categories, connecting millions of users with information and resources through its portfolio of iconic brands. This organisation is at the forefront of leveraging data to create highly personalised experiences for its audience.
The Role
Own the science behind recommendation engines that power personalised product feeds.
Design, build, evaluate, and continuously improve models for user taste across brand, category, color, price point, and fit.
Take recommendation problems from raw data to production models on an existing MLOps stack.
Address cold-start challenges with a small behavioral dataset and a catalog scaling to tens of millions of products.
Shape how millions of users discover products they love through foundational hires.
What You'll Need
Master's degree or higher in Computer Science, Statistics, Machine Learning, Applied Mathematics, or related quantitative field, or equivalent practical experience.
Strong data science fundamentals: statistics, experimental design, and evaluation methodology.
Demonstrated ownership of the full A/B testing lifecycle, including design, execution, and interpretation.
Experience designing, training, and deploying embedding models and vector retrieval for product or content similarity at scale.
Direct experience with cold-start / sparse-signal personalization.
Strong Python and modern ML frameworks (PyTorch, TensorFlow, or JAX), with an emphasis on production-quality code.
Strong SQL skills for querying large datasets in a cloud data warehouse (BigQuery preferred).
Experience deploying and serving models on a cloud ML platform, with Google Cloud Platform Vertex AI strongly preferred.
Commerce intuition and understanding of merchandising, category, and product management concerns.
Curiosity and pragmatism about emerging AI, particularly LLMs and modern retrieval/ranking.
Strong written and verbal communication, able to explain technical tradeoffs to both technical and non-technical stakeholders.
What's On Offer
Opportunity to work on a foundational role shaping user experiences.
A hands-on, full-cycle role with ownership of the model layer.
Collaboration with MLOps, engineering, and product teams.
Flexibility for remote work with hybrid options if commutable to New York.
Apply via Haystack today!
Responsibilities
- Own the science behind recommendation engines that power personalised product feeds
- Design, build, evaluate, and continuously improve models for user taste
- Take recommendation problems from raw data to production models
- Address cold-start challenges with a small behavioral dataset
Qualifications
- Master's degree or higher in a quantitative field or equivalent practical experience
- Strong data science fundamentals: statistics, experimental design, and evaluation methodology
- Demonstrated ownership of the full A/B testing lifecycle
- Experience designing, training, and deploying embedding models
- Strong Python and modern ML frameworks experience
Benefits
- Opportunity to work on a foundational role shaping user experiences
- Collaboration with MLOps, engineering, and product teams
- Flexibility for remote work with hybrid options
Skills mentioned
About Haystack
Haystack combines AI & expert vetting to deliver world-class tech candidates who are engaged, aligned, and ready to interview. We're trusted by over 400,000+ tech candidates, working in Software Engineering, Data, Design, DevOps, Cloud, Tech Management, Testing, Product & Delivery, Architecture and more. 100s of employers from startups and scale-ups like Atom Bank, DuckDuckGo and Goodlord to established enterprises like American Express, Dunelm and AWS use Haystack to connect with qualified tech talent that they can't find anywhere else.