Senior Data Scientist
Senior Data Scientist
Posted today
SENIORITY
Lead
About the role
- Lead design, development, and deployment of AI applications across multiple business domains
- Own delivery accountability across planning, execution, testing, and production rollout
- Design and implement AI-powered solutions, including: (LLMs, prompt engineering, RAG pipelinesEvaluate and adopt emerging AI technologies (e.g., Copilot, Foundry, open-source frameworks) Python (FastAPI, data pipelines, AI/ML frameworks) Cloud-native patterns (Azure/AWS/GCP)
- Ensure system observability (logging, monitoring, alerting)
- Coordinates and reviews data collection, trend identification, and pattern recognition, using advanced techniques to drive decision making and identification of data driven insights
- Contributes to the adoption of enterprise information products through communicating in a clear manner how enterprise information products answer material banking questions leading to decisions and actions
- Applies agile practices for project management, solution development, deployment, and maintenance
- Provides oversight and support of technical documentation, capturing the business requirements, and specifications related to the developed analytical solution, and implementation in production
- Reviews work products to ensure adequate quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment
- Mitigates risk by identifying potential issues and developing controls
- Possesses deep knowledge and subject-matter expertise of the latest advances in the fields of data science and artificial intelligence to support business analytics
- Lead end-to-end delivery of AI and non-AI software solutions across multiple projects
- Design and implement scalable architectures (microservices, cloud-native, event-driven)
- Build and maintain backend systems using Java and Python
- Develop and integrate AI solutions (LLMs, RAG, agents, ML pipelines) into enterprise platforms
- 10+ years of experience in software engineering and system design
- Proven experience delivering large-scale enterprise applications and AI solutions
- Technical SkillsPython (AI/ML, APIs, data engineering)
- Hands-on experience with: AI/ML frameworks (OpenAI, Hugging Face, LangChain, etc.)RAG pipelines, embeddings, vector databasesRESTful APIs, distributed systems
- Architecture & Platform Skills
- Microservices, APIs, event-driven architectures
- Cloud platforms (Azure preferred)
- Containerization (Docker, Kubernetes)AI/ML KnowledgeLLM-based applications and prompt engineering
- Model lifecycle management (training, deployment, monitoring)AI governance, risk, and explainability (preferred in regulated industries)
- Soft SkillsStrong problem-solving and analytical thinking
- Excellent communication and stakeholder management
- Ability to operate in a fast-paced, ambiguous environment
- Experience in financial services or regulated industries
- Exposure to Microsoft ecosystem (Copilot Studio, Foundry, Fabric)
- Familiarity with agent orchestration, MCP, and AI platform integration patterns
- Experience with data privacy, compliance, and secure AI deployments
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
