Data Scientist & Engineer

Norton Rose Fulbright; City Of London; Hybrid; GBP 60,000 - 90,000; Full time

Job summary

Norton Rose Fulbright LLP is building a new R&D data capability focused on data-driven and AI-enabled products for legal services and the wider business of law. The Data Scientist & Engineer will design, build and operate data pipelines in Microsoft Fabric and Databricks, turning priority sources into governed, reusable data assets and analytic products.

You will join a hands-on team collaborating across discovery, prototyping, engineering, productionisation and continuous improvement,

Qualifications

• Experience building data pipelines and data assets.
• Proficiency with data quality, lineage, and governance.
• Experience applying NLP/LLM techniques to large document datasets.
• Ability to publish datasets and features via databases, APIs or data products.

Responsibilities

• Design, build and operate data pipelines in Fabric and Databricks.
• Create lakehouse models with reusable features for entities (clients, matters, people).
• Implement data quality checks, lineage and observability.
• Conduct EDA and develop ML models for classification, ranking, forecasting or extraction.
• Apply NLP/LLM approaches for information extraction and clustering.
• Publish datasets and features through Fabric/Databricks data products.

Skills

Data science

Data engineering

Microsoft Fabric

Databricks

Python

SQL

NLP

Machine learning models

Education

Bachelor's or Master's in CS/DS/Math/Statistics

Tools

Microsoft Fabric

Databricks

Python

SQL

Job description

We are building a new R&D capability focused on developing data-driven and AI-enabled products for legal services and the wider business of law.

The Data Scientist & Engineer will work within R&D alongside the Data Programme to build the foundational data capabilities required for those products: trusted, reusable data assets, reliable pipelines, data quality, lakehouse models and analytical products. These capabilities will support R&D products, AI applications, client intelligence and firm-wide decision support.

This is a hands-on hybrid data-engineering and applied-data-science role, with particular responsibility for building data products in Microsoft Fabric and Databricks. You will work with Data Programme colleagues to turn priority sources into governed, use-case-ready data assets using agreed patterns, without duplicating enterprise platform responsibilities.

You will join a small, hands-on multidisciplinary team working collaboratively across discovery, prototyping, engineering, productionisation and continuous improvement., Partner with the Data Programme, data owners and system teams to assess, access and combine priority internal and external data sources, understanding quality, permissions and fitness for use.

Design, build and operate reliable pipelines in Microsoft Fabric and Databricks to ingest, clean, standardise, enrich, version and publish structured, semi-structured and unstructured data as reusable data assets.

Create scalable lakehouse data models, schemas, data contracts and reusable features for entities such as clients, organisations, people, matters, sectors, jurisdictions, opportunities and legal topics.

Implement data-quality checks, lineage, provenance, observability, monitoring and change management within Fabric and Databricks workflows so data assets remain trusted over time.

Conduct exploratory data analysis to surface patterns, gaps, anomalies and data-quality issues, and identify opportunities for analysis, modelling or product use.

Develop, compare and validate appropriate statistical and machine-learning models for classification, ranking, recommendation, forecasting, anomaly detection, similarity or extraction problems.

Use NLP, embeddings and LLM-assisted techniques responsibly for classification, entity resolution, information extraction, clustering and relationship discovery across document-heavy data.

Publish curated datasets, features and analytical outputs through approved Fabric and Databricks data products, tables, APIs, search indexes, batch pipelines or product features.

Maintain reproducible code, tests, model and data documentation, evaluation evidence and clear statements of limitations and appropriate use.

Use AI agents and coding assistants responsibly to accelerate exploratory work, pipeline development, testing and documentation, while retaining ownership of analytical judgement and verification.

Initial Focus

Establish foundational, governed and permission-aware data assets in Microsoft Fabric and Databricks, including curated datasets, metadata, lakehouse data models and quality measures.

Develop reusable pipelines in Microsoft Fabric and Databricks for entity resolution, enrichment, metadata, relationship mapping and data-quality monitoring.

Run EDA and model development that increases the value of priority data assets for client intelligence, opportunity identification, pricing, matter analysis and other high-value use cases.

What Success Looks Like

The Data Programme and R&D teams can use documented, quality-controlled data assets in Fabric and Databricks without repeatedly cleaning and reconciling source data.

Analytical work identifies useful signals and viable opportunities, with transparent baselines, validation and limitations.

Norton Rose Fulbright is a global law firm with more than 3,000 lawyers advising clients across locations in the United States, Europe, Canada, Latin America, Asia, Australia, Africa and the Middle East. We provide a full scope of legal services to the world's preeminent corporations and financial institutions.

Our vision is to be a world class business, profitable, ambitious, cooperative and considerate, supporting our clients and people through our global business principles of Quality, Unity and Integrity.

With over 7,000 employees worldwide, our culture is the thread that connects we 

Because while individuals can do well, together we achieve something extraordinary.