At a Glance
- Tasks: Lead R&D initiatives in AI/ML for private credit analytics and fine-tune language models.
- Company: Innovative firm at the forefront of AI technology in finance.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on cutting-edge research and development.
- Why this job: Make a real impact by bridging research with practical applications in finance.
- Qualifications: 5+ years in data science with expertise in NLP and machine learning.
The predicted salary is between 70000 - 90000 £ per year.
We're looking for a Senior Data Scientist to lead R&D initiatives at the intersection of LLMs, information retrieval, and private credit analytics. You'll fine-tune small language models on financial documents, build agentic workflows for multi-step reasoning, and develop production-ready extraction systems that power our AI platform for institutional investors. This role bridges cutting‑edge research with real‑world deployment. You'll work closely with Prompt Engineers on hybrid LLM+ML approaches, partner with QA Data on evaluation frameworks, and translate research into detailed specs for our Platform Engineering team. Your models will process thousands of credit agreements daily, requiring both innovation and reliability.
What You'll Do
- Fine‑tune Small Language Models on proprietary private credit corpus (credit agreements, indentures, term sheets)
- Develop information retrieval systems: semantic search, ranking algorithms, and context‑aware retrieval
- Build agentic workflows with multi-step reasoning, tool use, reflection, and self‑correction capabilities
- Train classification models for document type identification, section detection, and entity recognition
- Create extraction models: NER for financial entities, relation extraction, structured table parsing
- Partner with Prompt Engineers on prompt optimization strategies and hybrid LLM+ML approaches
- Experiment with latest techniques: RAG architectures, fine‑tuning methods (LoRA, QLoRA), model distillation
- Present research findings to engineering team and stakeholders monthly (progress, insights, recommendations)
- Stay current with academic research and industry developments in NLP, LLMs, and financial ML
Production Readiness & Deployment
- Write detailed technical specs for Platform team: model architecture, dependencies, deployment steps, API contracts
- Define production readiness criteria: performance benchmarks, edge case handling, failover mechanisms, rollback procedures
- Create comprehensive model cards: intended use, limitations, bias analysis, performance metrics, monitoring requirements
- Optimize models for production constraints: latency 95%, cost
Senior Data Scientist (R&D) - AI/ML for Private Credit employer: Alphastream
Join a forward-thinking company that values innovation and collaboration, where as a Senior Data Scientist, you'll have the opportunity to lead groundbreaking R&D initiatives in AI/ML for private credit. Our dynamic work culture fosters continuous learning and professional growth, providing you with access to cutting-edge resources and a supportive team environment. Located in a vibrant city, we offer competitive benefits and a commitment to work-life balance, making us an exceptional employer for those seeking meaningful and impactful work.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist (R&D) - AI/ML for Private Credit
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI/ML and data science. We want to see how you’ve fine-tuned models or built workflows. A strong portfolio can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We recommend practising common interview questions and even doing mock interviews with friends. Confidence is key, so let’s make sure you’re ready to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search. Let’s get you on board!
We think you need these skills to ace Senior Data Scientist (R&D) - AI/ML for Private Credit
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with LLMs and financial analytics in your application. We want to see how you've tackled similar challenges in the past, so don’t hold back on those impressive projects!
Tailor Your Application:Customise your CV and cover letter to reflect the specific requirements of the Senior Data Scientist role. Use keywords from the job description to show us you understand what we're looking for and how you fit the bill.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see your qualifications and enthusiasm for the role!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Alphastream
✨Know Your Models Inside Out
Make sure you’re well-versed in the latest techniques for fine-tuning small language models, especially in the context of financial documents. Be ready to discuss your experience with RAG architectures and model distillation, as this will show your depth of knowledge and relevance to the role.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've developed information retrieval systems or built agentic workflows. Highlight any challenges you faced and how you overcame them, as this demonstrates your ability to innovate and adapt in real-world scenarios.
✨Communicate Clearly and Effectively
Since you'll be presenting research findings to engineering teams and stakeholders, practice explaining complex concepts in a straightforward manner. Use clear examples to illustrate your points, and be prepared to answer questions about your thought process and decision-making.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest developments in NLP, LLMs, and financial ML. Being able to discuss recent academic research or industry advancements will not only impress your interviewers but also show that you're passionate about the field and committed to continuous learning.
