Senior Data Scientist

Muzz; Greater London; On-site; GBP 90,000 - 135,000; Full time

Job summary

Muzz, based in London, is hiring a senior data scientist to drive personalization and product insights as we scale globally. You will own end-to-end ML projects, from problem framing to deployment, and mentor analysts and junior data scientists.

Join a profitable consumer tech startup backed by YC and help shape our data science roadmap while collaborating with product, engineering and growth teams to improve marketing and user experience.

Qualifications

• At least 6 years of experience in a Data Scientist or ML Engineer role.
• Strong Python and SQL knowledge.
• Solid grounding in personalization/recommendations methods (embeddings, ranking, collaborative filtering).
• Excellent written and verbal communication & ability to present to non-technical audiences.
• Commercial mindset with ability to harness customer insights to optimise marketing and products.
• Ability to work collaboratively in cross-functional teams.
• Passionate about solving complex data problems.
• Experience in designing and conducting A/B experiments.
• Proven track record of developing and owning production ML pipelines (data processing, deployment, monitoring, retraining).
• End-to-end ownership of significant ML projects from framing to shipping in live performance.

Responsibilities

• Join a dynamic data science team to grow the company and optimize products as we expand globally.
• Understand user behaviour to generate actionable product and marketing insights.
• Collaborate with product, engineering and growth teams.
• Drive innovation with a product-focused approach.
• Tackle a range of data to solve high-impact, complex challenges.
• Own and evolve production ML systems behind personalization and recommendations.
• Use AI tools to boost team productivity and set technical standards.
• Mentor analysts and data scientists and shape the team roadmap.

Skills

Python

SQL

Personalization

A/B testing

ML pipelines

Production ML

Cross-functional

Communication

Mentoring

Product mindset

Recommender systems

Mobile-first

BigQuery

Vertex AI

Tools

BigQuery

Vertex AI

Job description

We’re looking for a smart and ambitious data scientist, with real entrepreneurial flair to join our team and understand our members and all the metrics that matter. Love numbers and love being commercial? This role presents an opportunity to mold the future of the data science team, explore new ideas and new technologies.

Muzz is the world’s largest Muslim dating and marriage app. We’ve got over 15 million members and have helped more than 800,000 couples get married. We’re on our way to become the first $1 billion Muslim tech brand - but we need your help!

Day to day

• You'll be joining a dynamic data science team whose goal is to grow the company and optimize our products as we expand into new markets around the world
• You'll be understanding our user behaviour on the platform with a view to generating actionable insights in terms of both product and marketing
• You'll work closely with our product, engineering and growth teams
• You'll be a proactive self-starter, driving innovation with a product focus
• You’ll be diving into a range of data to solve our highest impact and complex challenges
• You'll own and evolve the production ML systems behind our personalization and recommendations serving millions of users
• You'll use AI tools as a core part of how you work and help set how the wider team gets the most out of them
• You'll raise the bar for the team - mentoring analysts and data scientists, and helping shape our technical standards and roadmap

Requirements

• At least 6 years of experience in a Data Scientist or Machine Learning Engineer role
• Strong Python and SQL knowledge
• Strong grounding in the statistical methods behind personalization and recommendations models - e.g. embeddings, ranking, collaborative filtering
• Excellent written and verbal communication skills and presenting to non-technical audiences
• Commercial mindset with the ability to harness customer insights to optimise our marketing and products
• Ability to work collaboratively in cross-functional teams
• Passionate about solving complex and challenging data problems
• Experience in designing and conducting A/B experiments
• A proven track record of developing and owning production ML pipelines - including data processing, deployment, monitoring, retraining
• Demonstrated end-to-end ownership of significant ML projects - from framing the problem to shipping it, and through the messy realities of live performance, edge cases and iteration once real users hit it

Nice to have

• Hands-on experience with recommender systems, with real-time or near-real-time updates and serving
• Experience in consumer-facing mobile-first products
• Experience with GCP platform - BigQuery/VertexAI

Why join Muzz?

We’re a profitable Consumer Tech startup, backed by Y Combinator (S17) and based in London. Join our fast growing team and work on an amazing product that’s changing the world.

• A great product - We’re the leading app in this space with over 15 million members worldwide and counting!
• Level up quickly - Work with talented, generous people on the kinds of challenges you’ll be proud to share.
• A diverse team - We have people from all walks of life all adding their unique perspective. Muslims and non-Muslims, cat lovers and dog lovers. Everyone is welcome!
• Meaningful equity - We’re all working together to succeed and everyone on the team gets a slice of the pie.
• A hackathon every quarter - We value curiosity and building something wacky (but useful!). Every quarter we organise into random teams and together we build, code, and prototype. Prizes and dinner complete the day!
• International travel - We fly the whole team to somewhere amazing twice a year to connect and have fun.
• Regular socials - Mini golf, hikes, super competitive Catan nights - we’ve done it all. Maybe you’ll be at the next social?
• Generous Holiday / PTO - All full-time members get at least 33 days of holiday, regardless of where they live.