Data Scientist
We are Printed.com, one of the largest and fastest growing on-line print shops in the UK. We are filled to the brim with a passionate team who are mad about printing, designing, building and growing the business. In the office you’ll find that we are forward-thinking, with a mission to be creative, innovative and to help our customers.
We are constantly investing in new products and using technology to improve how we increase our market share and take advantage of new opportunities. Catch us in our production space and you will find a fast-paced, dedicated team who endeavour to reach perfection for our customers.
We’re a growing company with offices in London and Newcastle, looking for employees that are equal parts dynamic and enthusiastic. People brimming over with new, original ideas that they just can’t wait to share with their team and bring to life.
We are seeking a Data Scientist with a strong technical background in machine learning and data analysis. In this role, you will be responsible for building and fine-tuning machine learning models that drive key business outcomes. These models will be integrated into various systems, including our website, reporting tools, and analytics platforms.You will work closely with the Data Engineering team to ensure the deployment, integration, and scaling of these models within our data infrastructure.
Key Responsibilities:
- Develop & Deploy ML Models: Build models that power personalization, recommendations, and anomaly detection.
- Implement ML Ops: Set up continuous integration, monitoring, and automated retraining for production models.
- Leverage AI Tools: Use AI-powered coding assistants (e.g., Cursor, Copilot) to enhance development efficiency.
- Collaborate: Work closely with data engineers and the Head of Data to ensure robust data pipelines and translate requirements into technical solutions.
*Candidates must be based in the UK*
Requirements- 3+ years’ experience in applied machine learning and production model deployment.
- Proficiency in Python, SQL, and ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Hands-on experience with AWS services and Databricks; familiarity with ML Ops principles is a plus.
- Ability to quickly learn new tools and independently deliver scalable, high-quality solutions.
- Experience with data pipelines (Kafka, Debezium, S3, Lambda, Delta Lake) is a bonus.
- Data Pipeline: Data sources → Debezium/Kafka → S3 → Databricks/Lambda → S3 (Delta format) / Embedded → Reporting/Notifications
- Infrastructure: AWS cloud managed via Terraform
- 22 days holiday (rising to 25 with service) Plus 8 days bank holidays
- Staff discounts & Friends and Family discounts
- Cycle to work scheme and Tech Scheme
- Breakfast and drinks provided
- Charity day per annum supported
- Summer and Christmas Parties
- Street food days
- Perkbox membership
- Enhanced Maternity & Paternity leave
- Employee referral scheme