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Senior Data Scientist

algo1

England

On-site

GBP 65,000 - 85,000

Full time

Today
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Job summary

A VC-backed startup in the UK seeks a Senior Data Scientist to work on advanced machine learning and data science solutions. The role involves building scalable machine learning systems for complex data analyses, translating machine learning advances into impactful products, and optimizing models for production. Candidates should have 3-5+ years of experience, an MSc in a relevant field, and expertise in Python. They offer competitive compensation, equity, and a collaborative work environment.

Benefits

Opportunity to build transformative technology
Real ownership and impact
Collaborative work environment
Competitive compensation
Equity in a growing company

Qualifications

  • 3-5+ years implementing advanced data science solutions in a commercial setting.
  • Strong foundational knowledge of machine learning and deep learning algorithms.
  • Expert-level proficiency in Python, with ability to develop production-grade code.

Responsibilities

  • Design and implement scalable machine learning for complex data analysis.
  • Translate advances in machine learning into impactful solutions and products.
  • Bring models to production and optimise for inference in edge environments.

Skills

Machine learning
Data analysis
Python
Data pipelines

Education

MSc in Computer Science, Machine Learning, or related field

Tools

Apache Spark
Kafka
Airflow
dbt
Job description
About Us

We are a VC-backed startup focused on behavioural AI, currently in stealth. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and Generative AI. Our platform is designed from the ground up - no legacy, no patchwork systems - just a clean slate and a clear vision. Our mission is to build products that customers love by harnessing cutting-edge AI to transform their shopping experience.

About the Job

We are looking for a Senior Data Scientist with experience in bringing advanced machine learning and data science systems to production to work with our team of industry leading domain experts and engineers. You'll be working across our entire data science stack, from advanced recommender systems to comprehensive performance analytics.

Key Responsibilities :
  • Design and implement scalable machine learning for complex data analysis, optimised recommendations, and predictive modelling.
  • Translate the latest advances in machine learning into impactful solutions and products, from rapid MVPs to fully deployed, production-ready systems.
  • Bring your models to production and optimise for inference in edge computing environments.
Essential Qualifications :
  • 3-5+ years implementing advanced data science solutions in a commercial setting.
  • MSc in Computer Science, Machine Learning, or a related field.
  • Experience building data pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt).
  • Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised / unsupervised learning, predictive analysis, and forecasting.
  • Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code.
Desired Skills (Bonus Points) :
  • Strong practical understanding of retail analytics including consumer segmentations, personalisation systems, campaign effectiveness and media measurement.
  • Experience with recommender systems and / or behavioural AI.
What We Offer :
  • Opportunity to build technology that will transform millions of shopping experiences
  • Real ownership and impact in shaping our product and company direction
  • A dynamic and collaborative work environment
  • A chance to work with cutting-edge technologies and solve challenging problems
  • Competitive compensation
  • Equity in a rapidly growing company

If you're an energetic data scientist who thrives in a fast-paced environment and wants to make a real impact on the future of retail, we encourage you to apply.

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