Data Scientist

BDO; City Of London; Hybrid; GBP 101,000 - 166,000; Full time

Job summary

BDO Regulatory Solutions in London is seeking a Data Scientist for an initial 5‑month contract starting in November, with a competitive day rate via umbrella employment. You will join the delivery team to develop models, maintain documentation and productionise services, leveraging AI/ML and risk analytics.

Required skills include Python, SQL and time-series analysis, plus experience with model deployment, Git and graph technologies.

Qualifications

• Experience building models, documenting workflows and deploying productionised services.
• Solid knowledge of AI/ML techniques and time-series risk analysis.
• Experience in RegTech/FinCrime or data-led supervision is a plus.

Responsibilities

• Use Python for data wrangling, modeling and feature engineering.
• Query structured data sources with SQL and perform EDA.
• Develop and validate models including classification and unsupervised tasks.
• Deploy ML solutions with containerised pipelines and monitor drift.
• Collaborate with delivery teams and maintain reproducible workflows.

Skills

Python

SQL

Time-series analysis

EDA

Model development

Version control

ML deployment

Graph analytics

Tools

Neo4j

Neptune

Gremlin/Cypher

Git

Container technologies (Podman/SageMaker)

Job description

Data Scientist - London - Hybrid

Job description

BDO Regulatory Solutions are currently recruiting for a Data Scientist to join our client, a Regulated firm, based in London.

We are offering an initial contract starting in November through to 31st March 2027 initially with an excellent day rate, employed via an Umbrella company.

About the role:

We are looking for talented and experienced data scientists with experience to join our programme. To work with the existing delivery team to deliver models, documentation and associated productionised services. Solid knowledge and experience of AI and ML is essential

Key responsibilities include;

Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering.

SQL: For querying structured data sources

Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models.

Machine Learning Deployment: Familiarity with containerised deployment (e.g. Podman, SageMaker, DSW pipelines)

Version Control (Git): To maintain reproducible and collaborative workflows.

Time-Series Analysis: To assess risk trends over financial years.

Exploratory Data Analysis (EDA): To spot early signals or risk clusters.Desirable Experience:

Rank Aggregation/Ensemble Techniques: Understanding methods like Robust Rank Fusion (RRF)

Model Explainability Tools: e.g. SHAP, LIME to support interpretability.

Experience with Model Monitoring & Drift Detection

Experience in RegTech / FinCrime / Data-led Supervision Projects is a plus.

Experience developing solutions for record linkage and/or network analytics tasks.

Experience with graph query languages (e.g., Gremlin, Cypher), graph database platforms (e.g., Neptune, Neo4j), and/or graph visualisation platformsAdditional Information:

Location: London - Hybrid

Duration: Initial 5 months

Day Rate: Competitive, employed via an Umbrella company.