Data Science Engineer

Harnham; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Hybrid work

Cutting-edge AI initiatives

Ownership and visibility

Job summary

Harnham in London is seeking a data-focused professional to help shape AI-powered data foundations. You will join a newly established R&D function, building scalable data assets and owning projects end-to-end to drive real business impact.

Work in a small, collaborative team, collaborate with product and tech stakeholders, and influence technical direction while enjoying significant ownership and hybrid work options.

Qualifications

• Strong commercial experience spanning both Data Engineering and Data Science.
• Advanced Python, SQL and ideally PySpark.
• Hands-on experience with Microsoft Fabric and Databricks.
• Strong understanding of machine learning, feature engineering, model validation and statistical analysis.
• Experience building production-grade data pipelines and reusable data products.
• Exposure to NLP, document-heavy datasets, entity resolution or information extraction.
• Ability to communicate technical concepts clearly and translate business requirements into analytical solutions.
• Previous experience in a startup, scale-up, or small agile team environment would be highly beneficial.

Responsibilities

• Build and maintain scalable data pipelines using Microsoft Fabric and Databricks.
• Design reusable data assets, lakehouse models and analytical products.
• Conduct exploratory data analysis and uncover opportunities for modelling and insight generation.
• Develop and deploy machine learning solutions across structured and semi-structured data.
• Work on NLP, document-processing, entity resolution and information extraction use cases.
• Collaborate closely with technical and business stakeholders to solve complex problems.
• Apply engineering best practices including Git, testing, APIs and CI/CD.

Skills

Python

SQL

PySpark

ML concepts

NLP exposure

Tools

Databricks

Microsoft Fabric

Job description

Want to work at the intersection of Data Engineering, Data Science and AI? This is an opportunity to join a newly established R&D function where you'll help build the data foundations that power innovative AI products. Working in a small, highly collaborative team, you'll have the chance to influence technical direction, own projects end-to-end, and create scalable data assets that drive real business impact.

The Company

They are investing heavily in Data and AI, building a new capability focused on developing data-driven products and intelligent solutions. The team is intentionally small and multidisciplinary, bringing together expertise across Data Science, Data Engineering, AI and Product Development. This is a hands-on environment where collaboration, autonomy and continuous learning are highly valued. Candidates who enjoy startup-style ownership and working in agile teams are likely to thrive.

The Role

• Build and maintain scalable data pipelines using Microsoft Fabric and Databricks.
• Design reusable data assets, lakehouse models and analytical products.
• Conduct exploratory data analysis and uncover opportunities for modelling and insight generation.
• Develop and deploy machine learning solutions across structured and semi-structured data.
• Work on NLP, document-processing, entity resolution and information extraction use cases.
• Collaborate closely with technical and business stakeholders to solve complex problems.
• Apply engineering best practices including Git, testing, APIs and CI/CD.

Your Skills & Experience

• Strong commercial experience spanning both Data Engineering and Data Science.
• Advanced Python, SQL and ideally PySpark.
• Hands-on experience with Microsoft Fabric and Databricks.
• Strong understanding of machine learning, feature engineering, model validation and statistical analysis.
• Experience building production-grade data pipelines and reusable data products.
• Exposure to NLP, document-heavy datasets, entity resolution or information extraction.
• Ability to communicate technical concepts clearly and translate business requirements into analytical solutions.
• Previous experience in a startup, scale-up, or small agile team environment would be highly beneficial.

What They Offer

• Hybrid working arrangement.
• Opportunity to work on cutting-edge Data and AI initiatives.
• Significant ownership and visibility within a growing function.
• Clear progression and exposure to senior Data, AI and R&D leaders.