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Senior Data Scientist BN_28/10/2026
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Employment terms need review — employment source
Employment type Permanent contract & B2B
Read the full posting
What you’ll work on
Full postingDesign and develop LLM-based agentic solutions to automate business processes
Develop data extraction pipelines for AI workflows
Implement evaluation and observability frameworks for AI agents
Deploy and industrialize LLMs and models on GPUs with testing and DevOps practices
Work with business teams to identify needs and drive AI adoption
From the employer’s posting
Design and develop LLM-based agentic solutions to automate complex business processes.
Develop data extraction pipelines and implement evaluation and observability frameworks for AI agents.
implement evaluation and observability frameworks for AI agents.
Deploy and industrialize models (LLMs, GPUs), ensuring quality through testing and DevOps best practices
Work closely with business teams to identify needs and drive the adoption of AI solutions.
Posting record
Report an errorActively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 20266 days ago
- Recorded sightings
- 6
- Last seen by us
- Nov 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Margo-Group is hiring
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Its jobs tend to stay up a long time
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Bash
- Python
- Kubernetes
- FastAPI
Where the posting names them
- Hands-on practice in pytest (unit, functional, and integration testing for ML/LLM pipelines). - Bash scripts for automation, data handling, and container interaction. - LLMs Architecture understanding proven by project portfolio.
Expectations: - Strong Python with extensive experience in Object-Oriented Programming and enterprise software design patterns. - Proven track record building asynchronous microservices and endpoints using FastAPI.
- Dedication to shipping stable, secure code into flagship banking infrastructure where compliance, auditability, and data security are non-negotiable. - General Stack: Google ADK, LangGraph, DSPy, vLLM, FastAPI, Python, Pytest. Arize Phoenix. Kubernetes, Jenkins, GPUs. Responsibilities:
- Strong Python with extensive experience in Object-Oriented Programming and enterprise software design patterns. - Proven track record building asynchronous microservices and endpoints using FastAPI. - Hands-on practice in pytest (unit, functional, and integration testing for ML/LLM pipelines).
Your next step
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About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
Context:
A team responsible for the development and industrialization of applications for the Investment Banking division. Accelerating the integration of generative AI solutions and AI agents into business processes. A strategic environment within the platform, with high-impact use cases in document analysis, credit, and finance.
Expectations:
- Strong Python with extensive experience in Object-Oriented Programming and enterprise software design patterns.
- Proven track record building asynchronous microservices and endpoints using FastAPI.
- Hands-on practice in pytest (unit, functional, and integration testing for ML/LLM pipelines).
- Bash scripts for automation, data handling, and container interaction.
- LLMs Architecture understanding proven by project portfolio.
- Architecting multi-step, stateful agentic graphs using LangGraph or Google ADK.
- Hands-on experience optimizing LLM pipelines programmatically using DSPy.
- Practical knowledge of deploying and running high-throughput open-weight models on GPU infrastructure using runtimes such as vLLM (experience with CUDA and fine-tuning is a strong plus).
- Hands-on familiarity with automated build, test, and release pipelines (Jenkins).
- Experience setting up tracing, drift detection, and automated evaluations for generative workflows using tools like Phoenix Arize.
- Dedication to shipping stable, secure code into flagship banking infrastructure where compliance, auditability, and data security are non-negotiable.
- General Stack: Google ADK, LangGraph, DSPy, vLLM, FastAPI, Python, Pytest. Arize Phoenix. Kubernetes, Jenkins, GPUs.
Responsibilities:
- Design and develop LLM-based agentic solutions to automate complex business processes.
- Work closely with business teams to identify needs and drive the adoption of AI solutions.
- Develop data extraction pipelines and implement evaluation and observability frameworks for AI agents.
- Deploy and industrialize models (LLMs, GPUs), ensuring quality through testing and DevOps best practices
- You are taking full ownership in driving AI features.
- You remember to respect the boundaries and non-deterministic nature of LLMs, communicate constraints clearly, and build robust safety rails.
- You are a team player, communicate technical trade-offs cleanly with architects and business users, and enjoy mentoring peers.
- You are testing ideas and PoCs quickly, validate feasibility with data and avoid technical debt.
Career Prospects:
- Build expertise in Agentic AI architectures and the industrialization of LLMs in production. Work on high-visibility projects within the Investment Banking division.
Employment type
Permanent contract & B2B
Source details
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- Pay
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- Location & working pattern
Warsaw
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- Work authorization
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