Quant jobs / SymphonyAI

Data Science Consultant

Develop AI and statistical models for SymphonyAI’s financial-services clients. The work covers financial-crime detection, trading surveillance and credit-risk applications.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Develop and evaluate statistical or ML solutions for client risk problems.
Build validated data pipelines and integrate models with systems.
Test explainability, fairness and production performance.

What they ask for

Required

Data science and machine learning
Python or similar modelling tools
SQL and databases
Client-facing delivery
Technical communication

Preferred

Financial regulatory workflows
Unix environments

Education: Bachelor’s in a quantitative subject; postgraduate study preferred.
Experience: 5–10 years in ML or data science; financial-services work must cover 3 or more years, with at least 2 years of client-facing delivery.
Languages and tools: Python
pandas
NumPy
scikit-learn
SQL

How to prepare

Validate an imbalanced financial-risk classifier.
Build explainability and drift checks for a deployed model.
Prototype a surveillance or credit-risk use case with reproducible evaluation.

What to study

The Model Validation Quant roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on SymphonyAI’s site before applying: requirements, location and pay can change after we check them.

View the posting on SymphonyAI’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with SymphonyAI and doesn’t handle applications.