Associate Data Scientist - GenAI & Advanced ML

Concirrus; London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading technology firm based in London is seeking a Data Scientist to develop and deploy innovative ML and GenAI-driven solutions. The ideal candidate should have a degree in a relevant field and professional experience in the ML lifecycle. Responsibilities include analyzing diverse datasets, implementing end-to-end models, and collaborating with product teams to enhance capabilities. This role offers flexible working arrangements and competitive compensation.

Benefits

Flexible working arrangements

Opportunities for professional growth

Competitive compensation

Comprehensive benefits

Qualifications

• Professional experience as a Data/ML Scientist, including end-to-end ML lifecycle.
• Strong Python skills, including pandas, numpy, scikit-learn.
• Experience building and deploying predictive models.

Responsibilities

• Analyse and model structured and unstructured data using advanced ML and GenAI techniques.
• Design, implement, and evaluate models end-to-end.
• Collaborate with Product teams to embed GenAI capabilities.

Skills

Python

Data wrangling

Feature engineering

Machine Learning

Problem-solving

Communication

Education

Degree in Maths, Computer Science, Data Science, or related field

Tools

scikit-learn

PyTorch

TensorFlow

Apache Spark

Job description

Overview

The Role

We are seeking a Data Scientist to join our rapidly expanding London-based team. At the heart of our mission is building products that solve real problems for our customers in commercial insurance. Our dynamic data platform, Quest, is evolving to integrate cutting-edge Generative AI capabilities, enabling next-generation insights, submission automation, and decision support.

You will be hands-on in developing and deploying ML and GenAI-driven solutions. Beyond predictive modelling, you’ll explore RAGs, semantic search, small language models (SLMs), embeddings, and fine-tuning techniques to maximise the value of diverse datasets, from commercial insurance to global sensor data. You’ll thrive interrogating structured and unstructured data, designing pipelines, and experimenting with new approaches that push the frontier of applied data science.

Responsibilities

• Work in a multi-disciplined team to deliver projects according to roadmap priorities.
• Analyse and model structured and unstructured data using advanced ML and GenAI techniques.
• Design, implement, and evaluate models end-to-end: data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• Apply RAG architectures, vector databases, embeddings, and semantic search to enrich products with context-aware AI.
• Fine-tune and optimise SLMs/LLMs for domain-specific tasks such as document classification, summarisation, and risk analysis.
• Research and prototype new approaches (e.g., prompt engineering, knowledge graph integration, hybrid search) to enhance product performance.
• Collaborate with Product teams to embed GenAI capabilities into Quest and generate new product opportunities.

Qualifications and Skills

Essential:

• Degree in Maths, Computer Science, Data Science, or related field.
• Professional experience as a Data/ML Scientist, including end-to-end ML lifecycle.
• Strong Python skills, including pandas, numpy, scikit-learn, and exposure to deep learning frameworks (PyTorch/TensorFlow).
• Experience building and deploying predictive models (classification, regression, clustering).
• Strong data wrangling, feature engineering, and problem-solving skills.
• Familiarity with embeddings, semantic similarity, or search techniques.
• Excellent self-management, prioritisation, and communication skills.

Nice to have:

• Experience with GenAI workflows: RAGs, prompt engineering, finetuning SLMs/LLMs.
• Exposure to vector databases (e.g., FAISS, Pinecone, Weaviate).
• Knowledge of transformers, sequence modelling, or NLP pipelines.
• Experience with cloud-based ML workflows (Azure AI, GCP Vertex AI, AWS Sagemaker).
• Experience with MLOps practices (CI/CD for ML, monitoring drift, prompt evaluation).
• Understanding of insurance-related risk modelling and underwriting processes.

Tools & Technologies

• Languages: Python, SQL, exposure to TypeScript or Java is a plus.
• ML/AI: scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain.
• Data: Apache Spark (PySpark), pandas, polars, numpy.
• GenAI-specific: Vector databases (FAISS, Pinecone, Weaviate), embeddings, RAG pipelines, fine-tuning frameworks.
• Cloud & Infra: GCP/Azure/AWS, Linux, distributed systems.

Concirrus

Concirrus is trusted by leading specialty insurers to enhance efficiency throughout the insurance lifecycle from acquisition to renewal. We automate processes such as submission ingestion, compliance checks, ESG monitoring, and portfolio management, allowing underwriters to focus on value-added activities. This results in increased operational efficiency and faster business acquisition.

Diversity, Equity & Inclusion (DE&I) Statement

We are committed to building a diverse team and fostering an inclusive environment where everyone feels empowered to do their best work. As we continue to grow and evolve, we pledge to:

• Provide a safe and welcoming workplace where all individuals feel valued and respected.
• Educate ourselves continuously and celebrate the unique perspectives that make us stronger.
• Ensure that our actions and behaviors align with our core values and commitment to DE&I.
• Regularly assess our progress and seek opportunities for ongoing improvement.

What We Offer

• A collaborative and innovative work environment where your contributions drive our success.
• Opportunities for professional growth and development.
• Flexible working arrangements, including the option to work from home up to three days per week, supporting a strong work-life balance.
• The opportunity to work with cutting-edge technology in a rapidly growing industry.
• Competitive compensation, comprehensive benefits, and a culture that values teamwork and innovation.